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compression</title> <meta name="description" content="Search results for: data compression"> <meta name="keywords" content="data compression"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="data compression"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 25866</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: data compression</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25866</span> Image Compression Using Block Power Method for SVD Decomposition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=El%20Asnaoui%20Khalid">El Asnaoui Khalid</a>, <a href="https://publications.waset.org/abstracts/search?q=Chawki%20Youness"> Chawki Youness</a>, <a href="https://publications.waset.org/abstracts/search?q=Aksasse%20Brahim"> Aksasse Brahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Ouanan%20Mohammed"> Ouanan Mohammed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=SVD" title=" SVD"> SVD</a>, <a href="https://publications.waset.org/abstracts/search?q=block%20SVD%20power%20method" title=" block SVD power method"> block SVD power method</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20compression" title=" lossless compression"> lossless compression</a>, <a href="https://publications.waset.org/abstracts/search?q=near%20lossless" title=" near lossless"> near lossless</a> </p> <a href="https://publications.waset.org/abstracts/34041/image-compression-using-block-power-method-for-svd-decomposition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34041.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">387</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25865</span> PEINS: A Generic Compression Scheme Using Probabilistic Encoding and Irrational Number Storage</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Jayashree">P. Jayashree</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Rajkumar"> S. Rajkumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20ratio" title="compression ratio">compression ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=generic%20compression" title=" generic compression"> generic compression</a>, <a href="https://publications.waset.org/abstracts/search?q=irrational%20number%20storage" title=" irrational number storage"> irrational number storage</a>, <a href="https://publications.waset.org/abstracts/search?q=probabilistic%20encoding" title=" probabilistic encoding"> probabilistic encoding</a> </p> <a href="https://publications.waset.org/abstracts/60542/peins-a-generic-compression-scheme-using-probabilistic-encoding-and-irrational-number-storage" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60542.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">294</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25864</span> Medical Image Compression Based on Region of Interest: A Review</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sudeepti%20Dayal">Sudeepti Dayal</a>, <a href="https://publications.waset.org/abstracts/search?q=Neelesh%20Gupta"> Neelesh Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In terms of transmission, bigger the size of any image, longer the time the channel takes for transmission. It is understood that the bandwidth of the channel is fixed. Therefore, if the size of an image is reduced, a larger number of data or images can be transmitted over the channel. Compression is the technique used to reduce the size of an image. In terms of storage, compression reduces the file size which it occupies on the disk. Any image is based on two parameters, region of interest and non-region of interest. There are several algorithms of compression that compress the data more economically. In this paper we have reviewed region of interest and non-region of interest based compression techniques and the algorithms which compress the image most efficiently. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20ratio" title="compression ratio">compression ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=region%20of%20interest" title=" region of interest"> region of interest</a>, <a href="https://publications.waset.org/abstracts/search?q=DCT" title=" DCT"> DCT</a>, <a href="https://publications.waset.org/abstracts/search?q=DWT" title=" DWT"> DWT</a> </p> <a href="https://publications.waset.org/abstracts/43380/medical-image-compression-based-on-region-of-interest-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43380.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">375</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25863</span> Learning Compression Techniques on Smart Phone</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farouk%20Lawan%20Gambo">Farouk Lawan Gambo</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamada%20Mohammad"> Hamada Mohammad </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20compression" title="data compression">data compression</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20preference" title=" learning preference"> learning preference</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20learning" title=" mobile learning"> mobile learning</a>, <a href="https://publications.waset.org/abstracts/search?q=multimedia" title=" multimedia"> multimedia</a> </p> <a href="https://publications.waset.org/abstracts/66086/learning-compression-techniques-on-smart-phone" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66086.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">447</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25862</span> A Deletion-Cost Based Fast Compression Algorithm for Linear Vector Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qiuxiao%20Chen">Qiuxiao Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Yan%20Hou"> Yan Hou</a>, <a href="https://publications.waset.org/abstracts/search?q=Ning%20Wu"> Ning Wu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Douglas-Peucker%20algorithm" title="Douglas-Peucker algorithm">Douglas-Peucker algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20vector%20data" title=" linear vector data"> linear vector data</a>, <a href="https://publications.waset.org/abstracts/search?q=compression" title=" compression"> compression</a>, <a href="https://publications.waset.org/abstracts/search?q=deletion%20cost" title=" deletion cost"> deletion cost</a> </p> <a href="https://publications.waset.org/abstracts/8376/a-deletion-cost-based-fast-compression-algorithm-for-linear-vector-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8376.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">251</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25861</span> A Survey on Lossless Compression of Bayer Color Filter Array Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alina%20Trifan">Alina Trifan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ant%C3%B3nio%20J.%20R.%20Neves"> António J. R. Neves</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Although most digital cameras acquire images in a raw format, based on a Color Filter Array that arranges RGB color filters on a square grid of photosensors, most image compression techniques do not use the raw data; instead, they use the rgb result of an interpolation algorithm of the raw data. This approach is inefficient and by performing a lossless compression of the raw data, followed by pixel interpolation, digital cameras could be more power efficient and provide images with increased resolution given that the interpolation step could be shifted to an external processing unit. In this paper, we conduct a survey on the use of lossless compression algorithms with raw Bayer images. Moreover, in order to reduce the effect of the transition between colors that increase the entropy of the raw Bayer image, we split the image into three new images corresponding to each channel (red, green and blue) and we study the same compression algorithms applied to each one individually. This simple pre-processing stage allows an improvement of more than 15% in predictive based methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bayer%20image" title="bayer image">bayer image</a>, <a href="https://publications.waset.org/abstracts/search?q=CFA" title=" CFA"> CFA</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20compression" title=" lossless compression"> lossless compression</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20coding%20standards" title=" image coding standards"> image coding standards</a> </p> <a href="https://publications.waset.org/abstracts/39918/a-survey-on-lossless-compression-of-bayer-color-filter-array-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39918.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">321</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25860</span> A High Compression Ratio for a Losseless Image Compression Based on the Arithmetic Coding with the Sorted Run Length Coding: Meteosat Second Generation Image Compression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cherifi%20Mehdi">Cherifi Mehdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahdir%20Mourad"> Lahdir Mourad</a>, <a href="https://publications.waset.org/abstracts/search?q=Ameur%20Soltane"> Ameur Soltane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image compression is the heart of several multimedia techniques. It is used to reduce the number of bits required to represent an image. Meteosat Second Generation (MSG) satellite allows the acquisition of 12 image files every 15 minutes and that results in a large databases sizes. In this paper, a novel image compression method based on the arithmetic coding with the sorted Run Length Coding (SRLC) for MSG images is proposed. The SRLC allows us to find the occurrence of the consecutive pixels of the original image to create a sorted run. The arithmetic coding allows the encoding of the sorted data of the previous stage to retrieve a unique code word that represents a binary code stream in the sorted order to boost the compression ratio. Through this article, we show that our method can perform the best results concerning compression ratio and bit rate unlike the method based on the Run Length Coding (RLC) and the arithmetic coding. Evaluation criteria like the compression ratio and the bit rate allow the confirmation of the efficiency of our method of image compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=arithmetic%20coding" title=" arithmetic coding"> arithmetic coding</a>, <a href="https://publications.waset.org/abstracts/search?q=Run%20Length%20Coding" title=" Run Length Coding"> Run Length Coding</a>, <a href="https://publications.waset.org/abstracts/search?q=RLC" title=" RLC"> RLC</a>, <a href="https://publications.waset.org/abstracts/search?q=Sorted%20Run%20Length%20Coding" title=" Sorted Run Length Coding"> Sorted Run Length Coding</a>, <a href="https://publications.waset.org/abstracts/search?q=SRLC" title=" SRLC"> SRLC</a>, <a href="https://publications.waset.org/abstracts/search?q=Meteosat%20Second%20Generation" title=" Meteosat Second Generation"> Meteosat Second Generation</a>, <a href="https://publications.waset.org/abstracts/search?q=MSG" title=" MSG"> MSG</a> </p> <a href="https://publications.waset.org/abstracts/16704/a-high-compression-ratio-for-a-losseless-image-compression-based-on-the-arithmetic-coding-with-the-sorted-run-length-coding-meteosat-second-generation-image-compression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16704.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">354</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25859</span> Representation Data without Lost Compression Properties in Time Series: A Review</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nabilah%20Filzah%20Mohd%20Radzuan">Nabilah Filzah Mohd Radzuan</a>, <a href="https://publications.waset.org/abstracts/search?q=Zalinda%20Othman"> Zalinda Othman</a>, <a href="https://publications.waset.org/abstracts/search?q=Azuraliza%20Abu%20Bakar"> Azuraliza Abu Bakar</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdul%20Razak%20Hamdan"> Abdul Razak Hamdan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20properties" title="compression properties">compression properties</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertainty" title=" uncertainty"> uncertainty</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertain%20time%20series" title=" uncertain time series"> uncertain time series</a>, <a href="https://publications.waset.org/abstracts/search?q=mining%20technique" title=" mining technique"> mining technique</a>, <a href="https://publications.waset.org/abstracts/search?q=weather%20prediction" title=" weather prediction"> weather prediction</a> </p> <a href="https://publications.waset.org/abstracts/1419/representation-data-without-lost-compression-properties-in-time-series-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1419.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">428</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25858</span> Compression Index Estimation by Water Content and Liquid Limit and Void Ratio Using Statistics Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lizhou%20Chen">Lizhou Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelhamid%20Belgaid"> Abdelhamid Belgaid</a>, <a href="https://publications.waset.org/abstracts/search?q=Assem%20Elsayed"> Assem Elsayed</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoming%20Yang"> Xiaoming Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20index" title="compression index">compression index</a>, <a href="https://publications.waset.org/abstracts/search?q=clay" title=" clay"> clay</a>, <a href="https://publications.waset.org/abstracts/search?q=settlement" title=" settlement"> settlement</a>, <a href="https://publications.waset.org/abstracts/search?q=consolidation" title=" consolidation"> consolidation</a>, <a href="https://publications.waset.org/abstracts/search?q=secondary%20compression%20index" title=" secondary compression index"> secondary compression index</a>, <a href="https://publications.waset.org/abstracts/search?q=soil%20parameter" title=" soil parameter"> soil parameter</a> </p> <a href="https://publications.waset.org/abstracts/111582/compression-index-estimation-by-water-content-and-liquid-limit-and-void-ratio-using-statistics-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/111582.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">163</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25857</span> Mobile Learning: Toward Better Understanding of Compression Techniques </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farouk%20Lawan%20Gambo">Farouk Lawan Gambo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data compression shrinks files into fewer bits then their original presentation. It has more advantage on internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature therefore making them difficult to digest by some students (Engineers in particular). To determine the best approach toward learning data compression technique, this paper first study the learning preference of engineering students who tend to have strong active, sensing, visual and sequential learning preferences, the paper also study the advantage that mobility of learning have experienced; Learning at the point of interest, efficiency, connection, and many more. A survey is carried out with some reasonable number of students, through random sampling to see whether considering the learning preference and advantages in mobility of learning will give a promising improvement over the traditional way of learning. Evidence from data analysis using Ms-Excel as a point of concern for error-free findings shows that there is significance different in the students after using learning content provided on smart phone, also the result of the findings presented in, bar charts and pie charts interpret that mobile learning has to be promising feature of learning. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20analysis" title="data analysis">data analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=compression%20techniques" title=" compression techniques"> compression techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20content" title=" learning content"> learning content</a>, <a href="https://publications.waset.org/abstracts/search?q=traditional%20learning%20approach" title=" traditional learning approach"> traditional learning approach</a> </p> <a href="https://publications.waset.org/abstracts/66857/mobile-learning-toward-better-understanding-of-compression-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66857.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">347</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25856</span> GPU Accelerated Fractal Image Compression for Medical Imaging in Parallel Computing Platform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md.%20Enamul%20Haque">Md. Enamul Haque</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20Al%20Kaisan"> Abdullah Al Kaisan</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmudur%20R.%20Saniat"> Mahmudur R. Saniat</a>, <a href="https://publications.waset.org/abstracts/search?q=Aminur%20Rahman"> Aminur Rahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we have implemented both sequential and parallel version of fractal image compression algorithms using CUDA (Compute Unified Device Architecture) programming model for parallelizing the program in Graphics Processing Unit for medical images, as they are highly similar within the image itself. There is several improvements in the implementation of the algorithm as well. Fractal image compression is based on the self similarity of an image, meaning an image having similarity in majority of the regions. We take this opportunity to implement the compression algorithm and monitor the effect of it using both parallel and sequential implementation. Fractal compression has the property of high compression rate and the dimensionless scheme. Compression scheme for fractal image is of two kinds, one is encoding and another is decoding. Encoding is very much computational expensive. On the other hand decoding is less computational. The application of fractal compression to medical images would allow obtaining much higher compression ratios. While the fractal magnification an inseparable feature of the fractal compression would be very useful in presenting the reconstructed image in a highly readable form. However, like all irreversible methods, the fractal compression is connected with the problem of information loss, which is especially troublesome in the medical imaging. A very time consuming encoding process, which can last even several hours, is another bothersome drawback of the fractal compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=accelerated%20GPU" title="accelerated GPU">accelerated GPU</a>, <a href="https://publications.waset.org/abstracts/search?q=CUDA" title=" CUDA"> CUDA</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20computing" title=" parallel computing"> parallel computing</a>, <a href="https://publications.waset.org/abstracts/search?q=fractal%20image%20compression" title=" fractal image compression"> fractal image compression</a> </p> <a href="https://publications.waset.org/abstracts/5645/gpu-accelerated-fractal-image-compression-for-medical-imaging-in-parallel-computing-platform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5645.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">336</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25855</span> Meteosat Second Generation Image Compression Based on the Radon Transform and Linear Predictive Coding: Comparison and Performance </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cherifi%20Mehdi">Cherifi Mehdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahdir%20Mourad"> Lahdir Mourad</a>, <a href="https://publications.waset.org/abstracts/search?q=Ameur%20Soltane"> Ameur Soltane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=radon%20transform" title=" radon transform"> radon transform</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20predictive%20coding%20%28LPC%29" title=" linear predictive coding (LPC)"> linear predictive coding (LPC)</a>, <a href="https://publications.waset.org/abstracts/search?q=run%20lengthcoding%20%28RLC%29" title=" run lengthcoding (RLC)"> run lengthcoding (RLC)</a>, <a href="https://publications.waset.org/abstracts/search?q=meteosat%20second%20generation%20%28MSG%29" title=" meteosat second generation (MSG)"> meteosat second generation (MSG)</a> </p> <a href="https://publications.waset.org/abstracts/16434/meteosat-second-generation-image-compression-based-on-the-radon-transform-and-linear-predictive-coding-comparison-and-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16434.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">421</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25854</span> An Online 3D Modeling Method Based on a Lossless Compression Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jiankang%20Wang">Jiankang Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hongyang%20Yu"> Hongyang Yu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a portable online 3D modeling method. The method first utilizes a depth camera to collect data and compresses the depth data using a frame-by-frame lossless data compression method. The color image is encoded using the H.264 encoding format. After the cloud obtains the color image and depth image, a 3D modeling method based on bundlefusion is used to complete the 3D modeling. The results of this study indicate that this method has the characteristics of portability, online, and high efficiency and has a wide range of application prospects. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=3D%20reconstruction" title="3D reconstruction">3D reconstruction</a>, <a href="https://publications.waset.org/abstracts/search?q=bundlefusion" title=" bundlefusion"> bundlefusion</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20compression" title=" lossless compression"> lossless compression</a>, <a href="https://publications.waset.org/abstracts/search?q=depth%20image" title=" depth image"> depth image</a> </p> <a href="https://publications.waset.org/abstracts/163266/an-online-3d-modeling-method-based-on-a-lossless-compression-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163266.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">82</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25853</span> Comparison of Compression Properties of Stretchable Knitted Fabrics and Bi-Stretch Woven Fabrics for Compression Garments</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Maqsood">Muhammad Maqsood</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasir%20Nawab"> Yasir Nawab</a>, <a href="https://publications.waset.org/abstracts/search?q=Syed%20Talha%20Ali%20Hamdani"> Syed Talha Ali Hamdani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stretchable fabrics have diverse applications ranging from casual apparel to performance sportswear and compression therapy. Compression therapy is the universally accepted treatment for the management of hypertrophic scarring after severe burns. Mostly stretchable knitted fabrics are used in compression therapy but in the recent past, some studies have also been found on bi-stretch woven fabrics being used as compression garments as they also have been found quite effective in the treatment of oedema. Therefore, the objective of the present study is to compare the compression properties of stretchable knitted and bi-stretch woven fabrics for compression garments. For this purpose four woven structures and four knitted structures were produced having the same areal density and their compression, comfort and mechanical properties were compared before and after 5, 10 and 15 washes. Four knitted structures used were single jersey, single locaste, plain pique and the honeycomb, whereas four woven structures produced were 1/1 plain, 2/1 twill, 3/1 twill and 4/1 twill. The compression properties of the produced samples were tested by using kikuhime pressure sensor and it was found that bi-stretch woven fabrics possessed better compression properties before and after washes and retain their durability after repeated use, whereas knitted stretchable fabrics lost their compression ability after repeated use and the required sub garment pressure of the knitted structures after 15 washes was almost half to that of woven bi-stretch fabrics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20garments" title="compression garments">compression garments</a>, <a href="https://publications.waset.org/abstracts/search?q=knitted%20structures" title=" knitted structures"> knitted structures</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20textiles" title=" medical textiles"> medical textiles</a>, <a href="https://publications.waset.org/abstracts/search?q=woven%20bi-stretch" title=" woven bi-stretch"> woven bi-stretch</a> </p> <a href="https://publications.waset.org/abstracts/39769/comparison-of-compression-properties-of-stretchable-knitted-fabrics-and-bi-stretch-woven-fabrics-for-compression-garments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39769.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">412</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25852</span> Compressed Suffix Arrays to Self-Indexes Based on Partitioned Elias-Fano</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guo%20Wenyu">Guo Wenyu</a>, <a href="https://publications.waset.org/abstracts/search?q=Qu%20Youli"> Qu Youli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compressed%20suffix%20array" title="compressed suffix array">compressed suffix array</a>, <a href="https://publications.waset.org/abstracts/search?q=self-indexing" title=" self-indexing"> self-indexing</a>, <a href="https://publications.waset.org/abstracts/search?q=partitioned%20Elias-Fano" title=" partitioned Elias-Fano"> partitioned Elias-Fano</a>, <a href="https://publications.waset.org/abstracts/search?q=PEF-CSA" title=" PEF-CSA"> PEF-CSA</a> </p> <a href="https://publications.waset.org/abstracts/65986/compressed-suffix-arrays-to-self-indexes-based-on-partitioned-elias-fano" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65986.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">252</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25851</span> Video Compression Using Contourlet Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Delara%20Kazempour">Delara Kazempour</a>, <a href="https://publications.waset.org/abstracts/search?q=Mashallah%20Abasi%20Dezfuli"> Mashallah Abasi Dezfuli</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20Javidan"> Reza Javidan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Video compression used for channels with limited bandwidth and storage devices has limited storage capabilities. One of the most popular approaches in video compression is the usage of different transforms. Discrete cosine transform is one of the video compression methods that have some problems such as blocking, noising and high distortion inappropriate effect in compression ratio. wavelet transform is another approach is better than cosine transforms in balancing of compression and quality but the recognizing of curve curvature is so limit. Because of the importance of the compression and problems of the cosine and wavelet transforms, the contourlet transform is most popular in video compression. In the new proposed method, we used contourlet transform in video image compression. Contourlet transform can save details of the image better than the previous transforms because this transform is multi-scale and oriented. This transform can recognize discontinuity such as edges. In this approach we lost data less than previous approaches. Contourlet transform finds discrete space structure. This transform is useful for represented of two dimension smooth images. This transform, produces compressed images with high compression ratio along with texture and edge preservation. Finally, the results show that the majority of the images, the parameters of the mean square error and maximum signal-to-noise ratio of the new method based contourlet transform compared to wavelet transform are improved but in most of the images, the parameters of the mean square error and maximum signal-to-noise ratio in the cosine transform is better than the method based on contourlet transform. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=video%20compression" title="video compression">video compression</a>, <a href="https://publications.waset.org/abstracts/search?q=contourlet%20transform" title=" contourlet transform"> contourlet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=discrete%20cosine%20transform" title=" discrete cosine transform"> discrete cosine transform</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a> </p> <a href="https://publications.waset.org/abstracts/6930/video-compression-using-contourlet-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6930.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">444</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25850</span> Image Compression Based on Regression SVM and Biorthogonal Wavelets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zikiou%20Nadia">Zikiou Nadia</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahdir%20Mourad"> Lahdir Mourad</a>, <a href="https://publications.waset.org/abstracts/search?q=Ameur%20Soltane"> Ameur Soltane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=2D%20discrete%20wavelet%20transform%20%28DWT-2D%29" title=" 2D discrete wavelet transform (DWT-2D)"> 2D discrete wavelet transform (DWT-2D)</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20regression%20%28SVR%29" title=" support vector regression (SVR)"> support vector regression (SVR)</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM%20Kernels" title=" SVM Kernels"> SVM Kernels</a>, <a href="https://publications.waset.org/abstracts/search?q=run-length" title=" run-length"> run-length</a>, <a href="https://publications.waset.org/abstracts/search?q=arithmetic%20coding" title=" arithmetic coding"> arithmetic coding</a> </p> <a href="https://publications.waset.org/abstracts/17954/image-compression-based-on-regression-svm-and-biorthogonal-wavelets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17954.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">382</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25849</span> QCARNet: Networks for Quality-Adaptive Compression Artifact</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seung%20Ho%20Park">Seung Ho Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Young%20Su%20Moon"> Young Su Moon</a>, <a href="https://publications.waset.org/abstracts/search?q=Nam%20Ik%20Cho"> Nam Ik Cho</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose a convolution neural network (CNN) for quality adaptive compression artifact reduction named QCARNet. The proposed method is different from the existing discriminative models that learn a specific model at a certain quality level. The method is composed of a quality estimation CNN (QECNN) and a compression artifact reduction CNN (CARCNN), which are two functionally separate CNNs. By connecting the QECNN and CARCNN, each CARCNN layer is able to adaptively reduce compression artifacts and preserve details depending on the estimated quality level map generated by the QECNN. We experimentally demonstrate that the proposed method achieves better performance compared to other state-of-the-art blind compression artifact reduction methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compression%20artifact%20reduction" title="compression artifact reduction">compression artifact reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=deblocking" title=" deblocking"> deblocking</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20denoising" title=" image denoising"> image denoising</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20restoration" title=" image restoration"> image restoration</a> </p> <a href="https://publications.waset.org/abstracts/108816/qcarnet-networks-for-quality-adaptive-compression-artifact" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108816.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">141</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25848</span> Objective Evaluation on Medical Image Compression Using Wavelet Transformation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amhimmid%20Mohammed%20Saffour">Amhimmid Mohammed Saffour</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20Mohamed%20Abdullah"> Mustafa Mohamed Abdullah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The use of computers for handling image data in the healthcare is growing. However, the amount of data produced by modern image generating techniques is vast. This data might be a problem from a storage point of view or when the data is sent over a network. This paper using wavelet transform technique for medical images compression. MATLAB program, are designed to evaluate medical images storage and transmission time problem at Sebha Medical Center Libya. In this paper, three different Computed Tomography images which are abdomen, brain and chest have been selected and compressed using wavelet transform. Objective evaluation has been performed to measure the quality of the compressed images. For this evaluation, the results show that the Peak Signal to Noise Ratio (PSNR) which indicates the quality of the compressed image is ranging from (25.89db to 34.35db for abdomen images, 23.26db to 33.3db for brain images and 25.5db to 36.11db for chest images. These values shows that the compression ratio is nearly to 30:1 is acceptable. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20image" title="medical image">medical image</a>, <a href="https://publications.waset.org/abstracts/search?q=Matlab" title=" Matlab"> Matlab</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title=" image compression"> image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%27s" title=" wavelet's"> wavelet's</a>, <a href="https://publications.waset.org/abstracts/search?q=objective%20evaluation" title=" objective evaluation"> objective evaluation</a> </p> <a href="https://publications.waset.org/abstracts/45414/objective-evaluation-on-medical-image-compression-using-wavelet-transformation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45414.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">285</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25847</span> Sainte Sophie Landfill: Field-Scale Assessment of Municipal Solid Waste Mechanical Characteristics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wameed%20Alghazali">Wameed Alghazali</a>, <a href="https://publications.waset.org/abstracts/search?q=Shawn%20Kenny"> Shawn Kenny</a>, <a href="https://publications.waset.org/abstracts/search?q=Paul%20J.%20Van%20Geel"> Paul J. Van Geel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Settlement of municipal solid waste (MSW) in landfills can be represented by mechanical settlement, which is instantaneous and time-dependent creep components, and biodegradation-induced settlement. Mechanical settlement is governed by the physical characteristics of MSW and the applied overburden pressure. Several research studies used oedometers and different size compression cells to evaluate the primary and mechanical creep compression indices/ratios. However, MSW is known for its heterogeneity, which means data obtained from laboratory testing are not necessary to be a good representation of the mechanical response observed in the field. Furthermore, most of the laboratory tests found in the literature were conducted on shredded samples of MSW to obtain specimens that are suitable for the testing setup. It is believed that shredding MSW samples changes the physical and mechanical properties of the waste. In this study, settlement field data was collected during the filling stage of Ste. Sophie landfill was used to estimate the primary and mechanical creep compression ratios. The field results from Ste. Sophie landfill indicated that both the primary and mechanical creep compression ratios of MSW are not constants but decrease with the increase in the applied vertical stress. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mechanical%20creep%20compression%20ratio" title="mechanical creep compression ratio">mechanical creep compression ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=municipal%20solid%20waste" title=" municipal solid waste"> municipal solid waste</a>, <a href="https://publications.waset.org/abstracts/search?q=primary%20compression%20ratio" title=" primary compression ratio"> primary compression ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=stress%20level" title=" stress level"> stress level</a> </p> <a href="https://publications.waset.org/abstracts/162606/sainte-sophie-landfill-field-scale-assessment-of-municipal-solid-waste-mechanical-characteristics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162606.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">94</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25846</span> A Method for Compression of Short Unicode Strings</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Masoud%20Abedi">Masoud Abedi</a>, <a href="https://publications.waset.org/abstracts/search?q=Abbas%20Malekpour"> Abbas Malekpour</a>, <a href="https://publications.waset.org/abstracts/search?q=Peter%20Luksch"> Peter Luksch</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Reza%20Mojtabaei"> Mohammad Reza Mojtabaei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The use of short texts in communication has been greatly increasing in recent years. Applying different languages in short texts has led to compulsory use of Unicode strings. These strings need twice the space of common strings, hence, applying algorithms of compression for the purpose of accelerating transmission and reducing cost is worthwhile. Nevertheless, other compression methods like gzip, bzip2 or PAQ due to high overhead data size are not appropriate. The Huffman algorithm is one of the rare algorithms effective in reducing the size of short Unicode strings. In this paper, an algorithm is proposed for compression of very short Unicode strings. At first, every new character to be sent to a destination is inserted in the proposed mapping table. At the beginning, every character is new. In case the character is repeated for the same destination, it is not considered as a new character. Next, the new characters together with the mapping value of repeated characters are arranged through a specific technique and specially formatted to be transmitted. The results obtained from an assessment made on a set of short Persian and Arabic strings indicate that this proposed algorithm outperforms the Huffman algorithm in size reduction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Algorithms" title="Algorithms">Algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=Data%20Compression" title=" Data Compression"> Data Compression</a>, <a href="https://publications.waset.org/abstracts/search?q=Decoding" title=" Decoding"> Decoding</a>, <a href="https://publications.waset.org/abstracts/search?q=Encoding" title=" Encoding"> Encoding</a>, <a href="https://publications.waset.org/abstracts/search?q=Huffman%20Codes" title=" Huffman Codes"> Huffman Codes</a>, <a href="https://publications.waset.org/abstracts/search?q=Text%20Communication" title=" Text Communication"> Text Communication</a> </p> <a href="https://publications.waset.org/abstracts/66703/a-method-for-compression-of-short-unicode-strings" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66703.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">348</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25845</span> In-Situ Quasistatic Compression and Microstructural Characterization of Aluminium Foams of Different Cell Topology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Islam">M. A. Islam</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20J.%20Hazell"> P. J. Hazell</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20P.%20Escobedo"> J. P. Escobedo</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Saadatfar"> M. Saadatfar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quasistatic compression and micro structural characterization of closed cell aluminium foams of different pore size and cell distributions has been carried out. Metallic foams have good potential for lightweight structures for impact and blast mitigation and therefore it is important to find out the optimized foam structure (i.e. cell size, shape, relative density, and distribution) to maximize energy absorption. In this paper, we present results for two different aluminium metal foams of density 0.5 g/cc and 0.7 g/cc respectively that have been tested in quasi-static compression. The influence of cell geometry and cell topology on quasistatic compression behavior has been investigated using computed tomography (micro-CT) analysis. The compression behavior and micro structural characterization will be presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=metal%20foams" title="metal foams">metal foams</a>, <a href="https://publications.waset.org/abstracts/search?q=micro-CT" title=" micro-CT"> micro-CT</a>, <a href="https://publications.waset.org/abstracts/search?q=cell%20topology" title=" cell topology"> cell topology</a>, <a href="https://publications.waset.org/abstracts/search?q=quasistatic%20compression" title=" quasistatic compression"> quasistatic compression</a> </p> <a href="https://publications.waset.org/abstracts/11025/in-situ-quasistatic-compression-and-microstructural-characterization-of-aluminium-foams-of-different-cell-topology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11025.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">455</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25844</span> Application of Compressed Sensing Method for Compression of Quantum Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Kowalski">M. Kowalski</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20%C5%BByczkowski"> M. Życzkowski</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Karol"> M. Karol</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Current quantum key distribution systems (QKD) offer low bit rate of up to single MHz. Compared to conventional optical fiber links with multiple GHz bitrates, parameters of recent QKD systems are significantly lower. In the article we present the conception of application of the Compressed Sensing method for compression of quantum information. The compression methodology as well as the signal reconstruction method and initial results of improving the throughput of quantum information link are presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quantum%20key%20distribution%20systems" title="quantum key distribution systems">quantum key distribution systems</a>, <a href="https://publications.waset.org/abstracts/search?q=fiber%20optic%20system" title=" fiber optic system"> fiber optic system</a>, <a href="https://publications.waset.org/abstracts/search?q=compressed%20sensing" title=" compressed sensing"> compressed sensing</a> </p> <a href="https://publications.waset.org/abstracts/9234/application-of-compressed-sensing-method-for-compression-of-quantum-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9234.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">693</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25843</span> Atomic Decomposition Audio Data Compression and Denoising Using Sparse Dictionary Feature Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=T.%20Bryan">T. Bryan </a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Kepuska"> V. Kepuska</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20Kostnaic"> I. Kostnaic</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A method of data compression and denoising is introduced that is based on atomic decomposition of audio data using “basis vectors” that are learned from the audio data itself. The basis vectors are shown to have higher data compression and better signal-to-noise enhancement than the Gabor and gammatone “seed atoms” that were used to generate them. The basis vectors are the input weights of a Sparse AutoEncoder (SAE) that is trained using “envelope samples” of windowed segments of the audio data. The envelope samples are extracted from the audio data by performing atomic decomposition with Gabor or gammatone seed atoms. This process identifies segments of audio data that are locally coherent with the seed atoms. Envelope samples are extracted by identifying locally coherent audio data segments with Gabor or gammatone seed atoms, found by matching pursuit. The envelope samples are formed by taking the kronecker products of the atomic envelopes with the locally coherent data segments. Oracle signal-to-noise ratio (SNR) verses data compression curves are generated for the seed atoms as well as the basis vectors learned from Gabor and gammatone seed atoms. SNR data compression curves are generated for speech signals as well as early American music recordings. The basis vectors are shown to have higher denoising capability for data compression rates ranging from 90% to 99.84% for speech as well as music. Envelope samples are displayed as images by folding the time series into column vectors. This display method is used to compare of the output of the SAE with the envelope samples that produced them. The basis vectors are also displayed as images. Sparsity is shown to play an important role in producing the highest denoising basis vectors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sparse%20dictionary%20learning" title="sparse dictionary learning">sparse dictionary learning</a>, <a href="https://publications.waset.org/abstracts/search?q=autoencoder" title=" autoencoder"> autoencoder</a>, <a href="https://publications.waset.org/abstracts/search?q=sparse%20autoencoder" title=" sparse autoencoder"> sparse autoencoder</a>, <a href="https://publications.waset.org/abstracts/search?q=basis%20vectors" title=" basis vectors"> basis vectors</a>, <a href="https://publications.waset.org/abstracts/search?q=atomic%20decomposition" title=" atomic decomposition"> atomic decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=envelope%20sampling" title=" envelope sampling"> envelope sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=envelope%20samples" title=" envelope samples"> envelope samples</a>, <a href="https://publications.waset.org/abstracts/search?q=Gabor" title=" Gabor"> Gabor</a>, <a href="https://publications.waset.org/abstracts/search?q=gammatone" title=" gammatone"> gammatone</a>, <a href="https://publications.waset.org/abstracts/search?q=matching%20pursuit" title=" matching pursuit"> matching pursuit</a> </p> <a href="https://publications.waset.org/abstracts/42586/atomic-decomposition-audio-data-compression-and-denoising-using-sparse-dictionary-feature-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42586.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">253</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25842</span> New Efficient Method for Coding Color Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Walaa%20M.Abd-Elhafiez">Walaa M.Abd-Elhafiez</a>, <a href="https://publications.waset.org/abstracts/search?q=Wajeb%20Gharibi"> Wajeb Gharibi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like, CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique which is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20image" title=" color image"> color image</a>, <a href="https://publications.waset.org/abstracts/search?q=q-coder" title=" q-coder"> q-coder</a>, <a href="https://publications.waset.org/abstracts/search?q=quantization" title=" quantization"> quantization</a>, <a href="https://publications.waset.org/abstracts/search?q=edge-detection" title=" edge-detection"> edge-detection</a> </p> <a href="https://publications.waset.org/abstracts/2342/new-efficient-method-for-coding-color-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2342.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">330</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25841</span> REDUCER: An Architectural Design Pattern for Reducing Large and Noisy Data Sets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Apkar%20Salatian">Apkar Salatian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To relieve the burden of reasoning on a point to point basis, in many domains there is a need to reduce large and noisy data sets into trends for qualitative reasoning. In this paper we propose and describe a new architectural design pattern called REDUCER for reducing large and noisy data sets that can be tailored for particular situations. REDUCER consists of 2 consecutive processes: Filter which takes the original data and removes outliers, inconsistencies or noise; and Compression which takes the filtered data and derives trends in the data. In this seminal article, we also show how REDUCER has successfully been applied to 3 different case studies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=design%20pattern" title="design pattern">design pattern</a>, <a href="https://publications.waset.org/abstracts/search?q=filtering" title=" filtering"> filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=compression" title=" compression"> compression</a>, <a href="https://publications.waset.org/abstracts/search?q=architectural%20design" title=" architectural design"> architectural design</a> </p> <a href="https://publications.waset.org/abstracts/2130/reducer-an-architectural-design-pattern-for-reducing-large-and-noisy-data-sets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2130.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">212</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25840</span> Scintigraphic Image Coding of Region of Interest Based on SPIHT Algorithm Using Global Thresholding and Huffman Coding</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Seddiki">A. Seddiki</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Djebbouri"> M. Djebbouri</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Guerchi"> D. Guerchi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Medical imaging produces human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rate but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in region of interest (ROI). This paper discusses a contribution to the lossless compression in the region of interest of Scintigraphic images based on SPIHT algorithm and global transform thresholding using Huffman coding. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=global%20thresholding%20transform" title="global thresholding transform">global thresholding transform</a>, <a href="https://publications.waset.org/abstracts/search?q=huffman%20coding" title=" huffman coding"> huffman coding</a>, <a href="https://publications.waset.org/abstracts/search?q=region%20of%20interest" title=" region of interest"> region of interest</a>, <a href="https://publications.waset.org/abstracts/search?q=SPIHT%20coding" title=" SPIHT coding"> SPIHT coding</a>, <a href="https://publications.waset.org/abstracts/search?q=scintigraphic%20images" title=" scintigraphic images"> scintigraphic images</a> </p> <a href="https://publications.waset.org/abstracts/17067/scintigraphic-image-coding-of-region-of-interest-based-on-spiht-algorithm-using-global-thresholding-and-huffman-coding" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17067.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">367</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25839</span> Normalized Compression Distance Based Scene Alteration Analysis of a Video</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lakshay%20Kharbanda">Lakshay Kharbanda</a>, <a href="https://publications.waset.org/abstracts/search?q=Aabhas%20Chauhan"> Aabhas Chauhan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an application of Normalized Compression Distance (NCD) to detect notable scene alterations occurring in videos is presented. Several research groups have been developing methods to perform image classification using NCD, a computable approximation to Normalized Information Distance (NID) by studying the degree of similarity in images. The timeframes where significant aberrations between the frames of a video have occurred have been identified by obtaining a threshold NCD value, using two compressors: LZMA and BZIP2 and defining scene alterations using Pixel Difference Percentage metrics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=Kolmogorov%20complexity" title=" Kolmogorov complexity"> Kolmogorov complexity</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20compression%20distance" title=" normalized compression distance"> normalized compression distance</a>, <a href="https://publications.waset.org/abstracts/search?q=root%20mean%20square%20error" title=" root mean square error"> root mean square error</a> </p> <a href="https://publications.waset.org/abstracts/54601/normalized-compression-distance-based-scene-alteration-analysis-of-a-video" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54601.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">340</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25838</span> Advantages of Electrifying Offshore Compression System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Siva%20Sankara%20Arudra">Siva Sankara Arudra</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamaruzaman%20Baharuddin"> Kamaruzaman Baharuddin</a>, <a href="https://publications.waset.org/abstracts/search?q=Ir.%20Ahmed%20Fadzil%20Mustafa%20Kamal"> Ir. Ahmed Fadzil Mustafa Kamal</a>, <a href="https://publications.waset.org/abstracts/search?q=Ir.%20Abdul%20Latif%20Mohamed"> Ir. Abdul Latif Mohamed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The advancement of electrical and electronics technologies has rewarded the oil and gas industry with great opportunities to embed more environmentally solutions into design. Most offshore oil and gas producers have their engineering and production asset goals to promote greater use of environmentally friendly compression system technologies to eliminate hazardous emissions from conventional gas compressor drivers. Therefore, this paper comprehensively elaborates the parametric study conducted in integrating the latest electrical and electronics drives technology into the existing compression system. This study was conducted in aspects of layout, reliability & availability, maintainability, emission, and cost. An existing offshore facility that utilized gas turbines as the driver for gas compression was set as Conventional Case for this study. The Electrification Case will utilize electric motor drives as the driver for the compression system. Findings from this study indicate more advantages in driver electrification compared to conventional compression systems. The findings of this paper can be set as a benchmark for future offshore driver selection for gas compression systems of similar operating parameters and power range. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=turbomachinery" title="turbomachinery">turbomachinery</a>, <a href="https://publications.waset.org/abstracts/search?q=electrification" title=" electrification"> electrification</a>, <a href="https://publications.waset.org/abstracts/search?q=emission" title=" emission"> emission</a>, <a href="https://publications.waset.org/abstracts/search?q=compression%20system" title=" compression system"> compression system</a> </p> <a href="https://publications.waset.org/abstracts/146076/advantages-of-electrifying-offshore-compression-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146076.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25837</span> Application of the Bionic Wavelet Transform and Psycho-Acoustic Model for Speech Compression </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chafik%20Barnoussi">Chafik Barnoussi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mourad%20Talbi"> Mourad Talbi</a>, <a href="https://publications.waset.org/abstracts/search?q=Adnane%20Cherif"> Adnane Cherif</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we propose a new speech compression system based on the application of the Bionic Wavelet Transform (BWT) combined with the psychoacoustic model. This compression system is a modified version of the compression system using a MDCT (Modified Discrete Cosine Transform) filter banks of 32 filters each and the psychoacoustic model. This modification consists in replacing the banks of the MDCT filter banks by the bionic wavelet coefficients which are obtained from the application of the BWT to the speech signal to be compressed. These two methods are evaluated and compared with each other by computing bits before and bits after compression. They are tested on different speech signals and the obtained simulation results show that the proposed technique outperforms the second technique and this in term of compressed file size. In term of SNR, PSNR and NRMSE, the outputs speech signals of the proposed compression system are with acceptable quality. In term of PESQ and speech signal intelligibility, the proposed speech compression technique permits to obtain reconstructed speech signals with good quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20compression" title="speech compression">speech compression</a>, <a href="https://publications.waset.org/abstracts/search?q=bionic%20wavelet%20transform" title=" bionic wavelet transform"> bionic wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=filterbanks" title=" filterbanks"> filterbanks</a>, <a href="https://publications.waset.org/abstracts/search?q=psychoacoustic%20model" title=" psychoacoustic model"> psychoacoustic model</a> </p> <a href="https://publications.waset.org/abstracts/1921/application-of-the-bionic-wavelet-transform-and-psycho-acoustic-model-for-speech-compression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1921.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">384</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=data%20compression&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=data%20compression&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=data%20compression&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=data%20compression&page=5">5</a></li> <li class="page-item"><a class="page-link" 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