Search results for: V. K. Ananthashayana

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K. Ananthashayana"> <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> 4</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: V. K. Ananthashayana</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> A Novel Recursive Multiplierless Algorithm for 2-D DCT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=V.K.Ananthashayana">V.K.Ananthashayana</a>, <a href="https://publications.waset.org/search?q=Geetha.K.S"> Geetha.K.S</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a recursive algorithm for the computation of 2-D DCT using Ramanujan Numbers is proposed. With this algorithm, the floating-point multiplication is completely eliminated and hence the multiplierless algorithm can be implemented using shifts and additions only. The orthogonality of the recursive kernel is well maintained through matrix factorization to reduce the computational complexity. The inherent parallel structure yields simpler programming and hardware implementation and provides log 1 2 3 2 N N-N+ additions and N N 2 log 2 shifts which is very much less complex when compared to other recent multiplierless algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=DCT" title="DCT">DCT</a>, <a href="https://publications.waset.org/search?q=Multilplerless" title=" Multilplerless"> Multilplerless</a>, <a href="https://publications.waset.org/search?q=Ramanujan%20Number" title=" Ramanujan Number"> Ramanujan Number</a>, <a href="https://publications.waset.org/search?q=Recursive." title=" Recursive."> Recursive.</a> </p> <a href="https://publications.waset.org/2219/a-novel-recursive-multiplierless-algorithm-for-2-d-dct" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/2219/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/2219/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/2219/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/2219/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/2219/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/2219/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/2219/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/2219/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/2219/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/2219/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/2219.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">1545</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Blind Source Separation Using Modified Gaussian FastICA</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=V.%20K.%20Ananthashayana">V. K. Ananthashayana</a>, <a href="https://publications.waset.org/search?q=Jyothirmayi%20M."> Jyothirmayi M.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses the problem of source separation in images. We propose a FastICA algorithm employing a modified Gaussian contrast function for the Blind Source Separation. Experimental result shows that the proposed Modified Gaussian FastICA is effectively used for Blind Source Separation to obtain better quality images. In this paper, a comparative study has been made with other popular existing algorithms. The peak signal to noise ratio (PSNR) and improved signal to noise ratio (ISNR) are used as metrics for evaluating the quality of images. The ICA metric Amari error is also used to measure the quality of separation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Amari%20error" title="Amari error">Amari error</a>, <a href="https://publications.waset.org/search?q=Blind%20Source%20Separation" title=" Blind Source Separation"> Blind Source Separation</a>, <a href="https://publications.waset.org/search?q=Contrast%0Afunction" title=" Contrast function"> Contrast function</a>, <a href="https://publications.waset.org/search?q=Gaussian%20function" title=" Gaussian function"> Gaussian function</a>, <a href="https://publications.waset.org/search?q=Independent%20Component%20Analysis." title=" Independent Component Analysis."> Independent Component Analysis.</a> </p> <a href="https://publications.waset.org/12887/blind-source-separation-using-modified-gaussian-fastica" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/12887/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/12887/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/12887/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/12887/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/12887/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/12887/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/12887/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/12887/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/12887/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/12887/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/12887.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">1743</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Joint Adaptive Block Matching Search (JABMS) Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=V.K.Ananthashayana">V.K.Ananthashayana</a>, <a href="https://publications.waset.org/search?q=Pushpa.M.K"> Pushpa.M.K</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper a new Joint Adaptive Block Matching Search (JABMS) algorithm is proposed to generate motion vector and search a best match macro block by classifying the motion vector movement based on prediction error. Diamond Search (DS) algorithm generates high estimation accuracy when motion vector is small and Adaptive Rood Pattern Search (ARPS) algorithm can handle large motion vector but is not very accurate. The proposed JABMS algorithm which is capable of considering both small and large motions gives improved estimation accuracy and the computational cost is reduced by 15.2 times compared with Exhaustive Search (ES) algorithm and is 1.3 times less compared with Diamond search algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Adaptive%20rood%20pattern%20search" title="Adaptive rood pattern search">Adaptive rood pattern search</a>, <a href="https://publications.waset.org/search?q=Block%20matching" title=" Block matching"> Block matching</a>, <a href="https://publications.waset.org/search?q=Diamond%20search" title=" Diamond search"> Diamond search</a>, <a href="https://publications.waset.org/search?q=Joint%20Adaptive%20search" title=" Joint Adaptive search"> Joint Adaptive search</a>, <a href="https://publications.waset.org/search?q=Motion%20estimation." title=" Motion estimation."> Motion estimation.</a> </p> <a href="https://publications.waset.org/13708/joint-adaptive-block-matching-search-jabms-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/13708/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/13708/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/13708/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/13708/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/13708/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/13708/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/13708/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/13708/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/13708/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/13708/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/13708.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">1693</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Super Resolution Blind Reconstruction of Low Resolution Images using Wavelets based Fusion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Liyakathunisa">Liyakathunisa</a>, <a href="https://publications.waset.org/search?q=V.%20K.%20Ananthashayana"> V. K. Ananthashayana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Crucial information barely visible to the human eye is often embedded in a series of low resolution images taken of the same scene. Super resolution reconstruction is the process of combining several low resolution images into a single higher resolution image. The ideal algorithm should be fast, and should add sharpness and details, both at edges and in regions without adding artifacts. In this paper we propose a super resolution blind reconstruction technique for linearly degraded images. In our proposed technique the algorithm is divided into three parts an image registration, wavelets based fusion and an image restoration. In this paper three low resolution images are considered which may sub pixels shifted, rotated, blurred or noisy, the sub pixel shifted images are registered using affine transformation model; A wavelet based fusion is performed and the noise is removed using soft thresolding. Our proposed technique reduces blocking artifacts and also smoothens the edges and it is also able to restore high frequency details in an image. Our technique is efficient and computationally fast having clear perspective of real time implementation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Affine%20Transforms" title="Affine Transforms">Affine Transforms</a>, <a href="https://publications.waset.org/search?q=Denoiseing" title=" Denoiseing"> Denoiseing</a>, <a href="https://publications.waset.org/search?q=DWT" title=" DWT"> DWT</a>, <a href="https://publications.waset.org/search?q=Fusion" title=" Fusion"> Fusion</a>, <a href="https://publications.waset.org/search?q=Image%20registration." title="Image registration.">Image registration.</a> </p> <a href="https://publications.waset.org/7195/super-resolution-blind-reconstruction-of-low-resolution-images-using-wavelets-based-fusion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/7195/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a 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Search results for: V. K. Ananthashayana