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href="#Objective_video_quality"> <div class="vector-toc-text"> <span class="vector-toc-numb">2</span> <span>Objective video quality</span> </div> </a> <button aria-controls="toc-Objective_video_quality-sublist" class="cdx-button cdx-button--weight-quiet cdx-button--icon-only vector-toc-toggle"> <span class="vector-icon mw-ui-icon-wikimedia-expand"></span> <span>Toggle Objective video quality subsection</span> </button> <ul id="toc-Objective_video_quality-sublist" class="vector-toc-list"> <li id="toc-Terminology" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Terminology"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.1</span> <span>Terminology</span> </div> </a> <ul id="toc-Terminology-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Classification_of_objective_video_quality_models" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Classification_of_objective_video_quality_models"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.2</span> <span>Classification of objective video quality models</span> </div> </a> <ul id="toc-Classification_of_objective_video_quality_models-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Use_of_picture_quality_models_for_video_quality_estimation" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Use_of_picture_quality_models_for_video_quality_estimation"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.3</span> <span>Use of picture quality models for video quality estimation</span> </div> </a> <ul id="toc-Use_of_picture_quality_models_for_video_quality_estimation-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Video_quality_artifacts" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Video_quality_artifacts"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.4</span> <span>Video quality artifacts</span> </div> </a> <ul id="toc-Video_quality_artifacts-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Examples_of_video_quality_metrics" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Examples_of_video_quality_metrics"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.5</span> <span>Examples of video quality metrics</span> </div> </a> <ul id="toc-Examples_of_video_quality_metrics-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Training_and_performance_evaluation" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Training_and_performance_evaluation"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.6</span> <span>Training and performance evaluation</span> </div> </a> <ul id="toc-Training_and_performance_evaluation-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Uses_and_application_of_objective_models" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Uses_and_application_of_objective_models"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.7</span> <span>Uses and application of objective models</span> </div> </a> <ul id="toc-Uses_and_application_of_objective_models-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Other_approaches" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Other_approaches"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.8</span> <span>Other approaches</span> </div> </a> <ul id="toc-Other_approaches-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Subjective_video_quality" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Subjective_video_quality"> <div class="vector-toc-text"> <span class="vector-toc-numb">3</span> <span>Subjective video quality</span> </div> </a> <ul id="toc-Subjective_video_quality-sublist" class="vector-toc-list"> </ul> </li> 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class="mw-body-content"><div class="mw-content-ltr mw-parser-output" lang="en" dir="ltr"><div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none">Perceived video degradation</div> <p><b>Video quality</b> is a characteristic of a <a href="/wiki/Video" title="Video">video</a> passed through a video transmission or processing system that describes perceived video degradation (typically compared to the original video). Video processing systems may introduce some amount of distortion or artifacts in the video signal that negatively impact the user's perception of the system. For many stakeholders in <a href="/wiki/Video_production" title="Video production">video production</a> and distribution, ensuring video quality is an important task. </p><p><b>Video quality evaluation</b> is performed to describe the quality of a set of video sequences under study. Video quality can be evaluated objectively (by <a href="/wiki/Mathematical_model" title="Mathematical model">mathematical models</a>) or subjectively (by asking users for their rating). Also, the quality of a system can be determined offline (i.e., in a laboratory setting for developing new codecs or services) or <a href="/wiki/In-service_program" title="In-service program">in-service</a> (to monitor and ensure a certain level of quality). </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="From_analog_to_digital_video">From analog to digital video</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=1" title="Edit section: From analog to digital video"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Since the world's first video sequence was recorded and transmitted, many video processing systems have been designed. Such systems <a href="/wiki/Video_codec" title="Video codec">encode video streams</a> and transmit them over various kinds of networks or channels. In the age of <a href="/wiki/Analog_video" class="mw-redirect" title="Analog video">analog video</a> systems, it was possible to evaluate the quality aspects of a video processing system by calculating the system's <a href="/wiki/Frequency_response" title="Frequency response">frequency response</a> using test signals (for example, a collection of color bars and circles). </p><p><a href="/wiki/Digital_video" title="Digital video">Digital video</a> systems have almost fully replaced analog ones, and quality evaluation methods have changed. The performance of a digital video processing and transmission system can vary significantly and depends on many factors, including the characteristics of the input video signal (e.g., amount of motion or spatial details), the settings used for encoding and transmission, and the channel fidelity or <a href="/wiki/Network_performance" title="Network performance">network performance</a>. </p> <div class="mw-heading mw-heading2"><h2 id="Objective_video_quality">Objective video quality</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=2" title="Edit section: Objective video quality"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p><b>Objective video quality models</b> are <a href="/wiki/Mathematical_model" title="Mathematical model">mathematical models</a> that approximate results from <a href="/wiki/Subjective_video_quality" title="Subjective video quality">subjective quality assessment</a>, in which human observers are asked to rate the quality of a video.<sup id="cite_ref-1" class="reference"><a href="#cite_note-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> In this context, the term <i>model</i> may refer to a simple statistical model in which several independent variables (e.g., the <a href="/wiki/Packet_loss" title="Packet loss">packet loss rate</a> on a network and the video coding parameters) are fit against results obtained in a subjective quality evaluation test using <a href="/wiki/Regression_analysis" title="Regression analysis">regression techniques</a>. A model may also be a more complicated algorithm implemented in <a href="/wiki/Software" title="Software">software</a> or <a href="/wiki/Electronic_hardware" title="Electronic hardware">hardware</a>. </p> <div class="mw-heading mw-heading3"><h3 id="Terminology">Terminology</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=3" title="Edit section: Terminology"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The terms <i>model</i> and <i>metric</i> are often used interchangeably in the field to mean a <a href="/wiki/Descriptive_statistic" class="mw-redirect" title="Descriptive statistic">descriptive statistic</a> that provides an <a href="/wiki/Indicator_(statistics)" title="Indicator (statistics)">indicator</a> of quality. The term “objective” refers to the fact that, in general, quality models are based on criteria that can be <i>measured</i> objectively, that is, free from human interpretation. They can be automatically evaluated by a <a href="/wiki/Computer_program" title="Computer program">computer program</a>. Unlike a panel of human observers, an objective model should always deterministically output the same quality score for a given set of input parameters. </p><p>Objective quality models are sometimes also referred to as <i>instrumental (quality) models</i>,<sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> in order to emphasize their application as measurement instruments. Some authors suggest that the term “objective” is misleading, as it “implies that instrumental measurements bear objectivity, which they only do in cases where they can be generalized.”<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Classification_of_objective_video_quality_models">Classification of objective video quality models</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=4" title="Edit section: Classification of objective video quality models"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <figure class="mw-default-size" typeof="mw:File/Thumb"><a href="/wiki/File:Objective_Video_Quality_Model_Classification.png" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/8/86/Objective_Video_Quality_Model_Classification.png/220px-Objective_Video_Quality_Model_Classification.png" decoding="async" width="220" height="87" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/8/86/Objective_Video_Quality_Model_Classification.png/330px-Objective_Video_Quality_Model_Classification.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/8/86/Objective_Video_Quality_Model_Classification.png/440px-Objective_Video_Quality_Model_Classification.png 2x" data-file-width="9300" data-file-height="3688" /></a><figcaption>Classification of objective video quality models into Full-Reference, Reduced-Reference and No-Reference.</figcaption></figure> <figure class="mw-default-size" typeof="mw:File/Thumb"><a href="/wiki/File:No-Reference_Image_and_video_quality_assessment.jpg" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/f/f1/No-Reference_Image_and_video_quality_assessment.jpg/220px-No-Reference_Image_and_video_quality_assessment.jpg" decoding="async" width="220" height="135" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/f/f1/No-Reference_Image_and_video_quality_assessment.jpg/330px-No-Reference_Image_and_video_quality_assessment.jpg 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/f/f1/No-Reference_Image_and_video_quality_assessment.jpg/440px-No-Reference_Image_and_video_quality_assessment.jpg 2x" data-file-width="1200" data-file-height="734" /></a><figcaption>No-reference image and video quality assessment methods.</figcaption></figure> <p>Objective models can be classified by the amount of information available about the original signal, the received signal, or whether there is a signal present at all:<sup id="cite_ref-:0_5-0" class="reference"><a href="#cite_note-:0-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> </p> <ul><li><b>Full Reference Methods (FR):</b> FR models compute the quality difference by comparing the original video signal against the received <a href="/wiki/Video_signal" class="mw-redirect" title="Video signal">video signal</a>. Typically, every pixel from the source is compared against the corresponding pixel in the received video, with no knowledge about the encoding or transmission process in between. More elaborate algorithms may choose to combine the pixel-based estimation with other approaches, such as those described below. FR models are usually the most accurate, at the expense of higher computational effort. As they require the availability of the original video before transmission or coding, they cannot be used in all situations (e.g., where the quality is measured from a client device).</li> <li><b>Reduced Reference Methods (RR):</b> RR models extract some features of both videos and compare them to give a quality score. They are used when all the original video is not available or when it would be practically impossible to do so, e.g., in a transmission with a limited bandwidth. This makes them more efficient than FR models at the expense of lower accuracy.</li> <li><b>No-Reference Methods (NR):</b> NR models try to assess the quality of a distorted video without any reference to the original signal. Due to the absence of an original signal, they may be less accurate than FR or RR approaches but are more efficient to compute. The Video Quality Experts Group has a dedicated working group on developing no-reference metrics (called <a rel="nofollow" class="external text" href="https://www.its.bldrdoc.gov/vqeg/projects/no-reference-metrics-norm.aspx">NORM</a>). <ul><li><b>Pixel-Based Methods (NR-P): </b>Pixel-based models use a decoded representation of the signal and analyze the quality based on the pixel information. Some of these evaluate specific degradation types only, such as blurring or other <a href="/wiki/Compression_artifact" title="Compression artifact">coding artifacts</a>.</li> <li><b>Parametric/Bitstream Methods (NR-B): </b>These models make use of features extracted from the transmission container and/or video bitstream, e.g., <a href="/wiki/Transport_Stream" class="mw-redirect" title="Transport Stream">MPEG-TS</a> packet headers, <a href="/wiki/Motion_vector" class="mw-redirect" title="Motion vector">motion vectors</a>, and quantization parameters. They do not have access to the original signal and require no decoding of the video, which makes them more efficient. In contrast to NR-P models, they have no access to the final decoded signal. In some cases, the prediction accuracy of bitstream-based metrics can reach one full reference without requiring a reference.<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup></li> <li><b>Hybrid Methods (Hybrid NR-P-B): </b>Hybrid models combine parameters extracted from the bitstream with a decoded video signal.<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> They are therefore a mix between the NR-P and NR-B models.</li></ul></li></ul> <div class="mw-heading mw-heading3"><h3 id="Use_of_picture_quality_models_for_video_quality_estimation">Use of picture quality models for video quality estimation</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=5" title="Edit section: Use of picture quality models for video quality estimation"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Some models that are used for video quality assessment (such as <a href="/wiki/Peak_signal-to-noise_ratio" title="Peak signal-to-noise ratio">PSNR</a> or <a href="/wiki/Structural_similarity" class="mw-redirect" title="Structural similarity">SSIM</a>) are simply <a href="/wiki/Image_quality" title="Image quality">image quality models</a>, whose output is calculated for every frame of a video sequence. An overview of recent no-reference <a href="/wiki/Image_quality" title="Image quality">image quality</a> models has also been given in a journal paper by Shahid et al.<sup id="cite_ref-:0_5-1" class="reference"><a href="#cite_note-:0-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> </p><p>The quality measure of every frame in a video (as determined by an image quality model) can then be recorded and pooled over time to assess the quality of an entire video sequence. While this method is easy to implement, it does not factor in certain kinds of degradations that develop over time, such as the moving artifacts caused by <a href="/wiki/Packet_loss" title="Packet loss">packet loss</a> and its <a href="/wiki/Packet_loss_concealment" title="Packet loss concealment">concealment</a>. A video quality model that considers the temporal aspects of quality degradations, like <a rel="nofollow" class="external text" href="https://its.ntia.gov/research-topics/video-quality-research/guides-and-tutorials/description-of-vqm-tools.aspx">VQM</a> or the <a href="/wiki/MOVIE_Index" title="MOVIE Index">MOVIE Index</a>, may be able to produce more accurate predictions of human-perceived quality. </p> <div class="mw-heading mw-heading3"><h3 id="Video_quality_artifacts">Video quality artifacts</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=6" title="Edit section: Video quality artifacts"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The estimation of <a href="/wiki/Visual_artifact" title="Visual artifact">visual artifacts</a> is a well known technique for estimating overall video quality. The majority of these artifacts are <a href="/wiki/Compression_artifact" title="Compression artifact">compression artifacts</a> caused by lossy compression. Some of the attributes typically estimated by pixel-based metrics include: </p><p><b>Spatial</b> </p> <ul><li><b>Blurring</b> — a result of loss of high spatial frequency image detail, usually at sharp edges.</li> <li><b>Blocking</b> — is caused by multiple algorithms because of the internal representation of an image with blocks size 8, 16, or 32. With specific parameters, they can average pixels inside a block making blocks distinct</li> <li><a href="/wiki/Ringing_artifacts" title="Ringing artifacts"><b>Ringing</b></a>, echoing or ghosting - takes the form of a “halo,” band, or “ghost” near sharp edges.</li> <li><b>Color bleeding</b> — occurs when the edges of one colour in the image unintentionally bleeds or overlaps into another colour</li> <li><b>Staircase noise</b> — is a special case of blocking along a diagonal or curved edge. Rather than rendering as smooth, it takes on the appearance of stair steps</li></ul> <p><b>Temporal</b> </p> <ul><li><b>Flickering</b> — is usually frequent brightness or colour changes along the time dimension. It is often broken out as fine-grain flickering and coarse-grain flickering.</li> <li><b>Mosquito noise</b> — a variant of flickering, it’s typified as haziness and/or shimmering around high-frequency content (sharp transitions between foreground entities and the background or hard edges).</li> <li><b>Floating</b> — refers to illusory motion in certain regions while the surrounding areas remain static. Visually, these regions appear as if they were floating on top of the surrounding background</li> <li><b>Jerkiness</b> or judder — is the perceived uneven or wobbly motion due to frame sampling. It’s often caused by the conversion of 24 fps movies to a 30 or 60 fps video format.</li></ul> <div class="mw-heading mw-heading3"><h3 id="Examples_of_video_quality_metrics">Examples of video quality metrics</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=7" title="Edit section: Examples of video quality metrics"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>This section lists examples of video quality metrics. </p> <style data-mw-deduplicate="TemplateStyles:r1236090951">.mw-parser-output .hatnote{font-style:italic}.mw-parser-output div.hatnote{padding-left:1.6em;margin-bottom:0.5em}.mw-parser-output .hatnote i{font-style:normal}.mw-parser-output .hatnote+link+.hatnote{margin-top:-0.5em}@media print{body.ns-0 .mw-parser-output .hatnote{display:none!important}}</style><div role="note" class="hatnote navigation-not-searchable plainlinks">This table is <a href="/wiki/Wikipedia:WikiProject_Lists#Incomplete_lists" title="Wikipedia:WikiProject Lists">incomplete</a>; you can help by <a class="external text" href="https://en.wikipedia.org/w/index.php?title=Video_quality&action=edit">expanding it</a>.</div> <table class="wikitable"> <tbody><tr> <th colspan="2">Metric</th> <th>Usage</th> <th>Description </th></tr> <tr> <th rowspan="5">Full-Reference </th> <td><a href="/wiki/PSNR" class="mw-redirect" title="PSNR">PSNR</a> (Peak Signal-to-Noise Ratio) </td> <td>Image</td> <td>It is calculated between every frame of the original and the degraded video signal. PSNR is the most widely used objective image quality metric. However, PSNR values do not correlate well with perceived picture quality due to the complex, highly non-linear behaviour of the human visual system. </td></tr> <tr> <td><a href="/wiki/SSIM" class="mw-redirect" title="SSIM">SSIM</a><sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> (Structural SIMilarity) </td> <td>Image</td> <td>SSIM is a perception-based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual phenomena, including both luminance masking and contrast masking terms. </td></tr> <tr> <td><a href="/wiki/MOVIE_Index" title="MOVIE Index">MOVIE Index</a><sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup> (MOtion-based Video Integrity Evaluation) </td> <td>Video</td> <td>The MOVIE index is a neuroscience-based model for predicting the perceptual quality of a (possibly compressed or otherwise distorted) motion picture or video against a pristine reference video. </td></tr> <tr> <td><a href="/wiki/VMAF" class="mw-redirect" title="VMAF">VMAF</a><sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> (Video Multimethod Assessment Fusion) </td> <td>Video</td> <td>VMAF uses different features to predict video quality, which are fused using a <a href="/wiki/Support-vector_machine" class="mw-redirect" title="Support-vector machine">SVM</a>-based regression to provide a single output score. These scores are then temporally pooled over the entire video sequence using the <a href="/wiki/Arithmetic_mean" title="Arithmetic mean">arithmetic mean</a> to provide an overall <a href="/wiki/Mean_opinion_score" title="Mean opinion score">mean opinion score</a> (MOS). </td></tr> <tr> <td>VQM<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup> </td> <td>Video </td> <td>This model has been standardized in ITU-T Rec. J.144 in 2001. </td></tr> <tr> <th rowspan="3">Reduced-Reference </th> <td>SRR<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup> (SSIM Reduced-Reference) </td> <td>Video</td> <td>SRR value is calculated as the ratio of received (target) video signal SSIM with reference video pattern SSIM values. </td></tr> <tr> <td>ST-RRED<sup id="cite_ref-13" class="reference"><a href="#cite_note-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> </td> <td>Video</td> <td>Compute wavelet coefficients of frame differences between the adjacent frames in a video sequence (modeled by a Gaussian Scale Mixture). It is used to evaluate RR entropic differences leading to temporal RRED.It in conjunction with spatial RRED indices evaluated by applying the RRED index on every frame of the video, yield the spatio-temporal RRED </td></tr> <tr> <td>ITU-T Rec. <a rel="nofollow" class="external text" href="https://www.itu.int/rec/T-REC-P.1204.4/en">P.1204.4</a> </td> <td>Video </td> <td>This reduced-reference model compares features extracted from a reference video with a distorted (compressed video).<sup id="cite_ref-:1_14-0" class="reference"><a href="#cite_note-:1-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup> </td></tr> <tr> <th rowspan="6">No-Reference </th> <td>NIQE<sup id="cite_ref-15" class="reference"><a href="#cite_note-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup> Naturalness Image Quality Evaluator </td> <td>Image</td> <td>This IQA model is founded on perceptually relevant spatial domain natural scene statistic (NSS) features extracted from local image patches that effectively capture the essential low-order statistics of natural images. </td></tr> <tr> <td>BRISQUE<sup id="cite_ref-16" class="reference"><a href="#cite_note-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> Blind/Referenceless Image Spatial Quality Evaluator </td> <td>Image</td> <td>The method extracts the pointwise statistics of local normalized luminance signals and measures image naturalness (or lack thereof) based on measured deviations from a natural image model. It also models the distribution of pairwise statistics of adjacent normalized luminance signals which provides distortion orientation information. </td></tr> <tr> <td>Video-BLIINDS<sup id="cite_ref-17" class="reference"><a href="#cite_note-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> </td> <td>Video</td> <td>Computes statistical models on DCT coefficients of frame differences and calculates motion characterization. Pedicts score based on those features using <a href="/wiki/Support-vector_machine" class="mw-redirect" title="Support-vector machine">SVM</a>. </td></tr> <tr> <td>ITU-T Rec. <a rel="nofollow" class="external text" href="https://www.itu.int/rec/T-REC-P.1203.1/en">P.1203.1</a> </td> <td>Video </td> <td>This is a metric that is part of the <a rel="nofollow" class="external text" href="https://www.itu.int/rec/T-REC-P.1203">P.1203</a> family of standards, which can use either metadata only (codec, resolution, bitrate, framerate), frame information (frame types and sizes), or the entire bitstream to analyze the quality of a compressed video. It is primarily intended to be used in the context of HTTP adaptive streaming. </td></tr> <tr> <td>ITU-T Rec. <a rel="nofollow" class="external text" href="https://www.itu.int/rec/T-REC-P.1204.3">P.1204.3</a> </td> <td>Video </td> <td>This model uses the video bitstream to analyze compression/coding quality based on features like quantization parameters and motion vectors.<sup id="cite_ref-:1_14-1" class="reference"><a href="#cite_note-:1-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup> </td></tr> <tr> <td>ITU-T Rec. <a rel="nofollow" class="external text" href="https://www.itu.int/rec/T-REC-P.1204.5">P.1204.5</a> </td> <td>Video </td> <td>This is a hybrid model that uses the decoded pixels and information about the video codec to determine final video quality.<sup id="cite_ref-:1_14-2" class="reference"><a href="#cite_note-:1-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup> </td></tr></tbody></table> <div class="mw-heading mw-heading3"><h3 id="Training_and_performance_evaluation">Training and performance evaluation</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=8" title="Edit section: Training and performance evaluation"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Since objective video quality models are expected to predict results given by human observers, they are developed with the aid of <a href="/wiki/Subjective_video_quality" title="Subjective video quality">subjective test results</a>. During the development of an objective model, its parameters should be trained so as to achieve the best correlation between the objectively predicted values and the subjective scores, often available as <a href="/wiki/Mean_opinion_score" title="Mean opinion score">mean opinion scores</a> (MOS). </p><p>The most widely used subjective test materials are in the public domain and include still pictures, motion pictures, streaming video, high definition, 3-D (stereoscopic), and special-purpose picture quality-related datasets.<sup id="cite_ref-18" class="reference"><a href="#cite_note-18"><span class="cite-bracket">[</span>18<span class="cite-bracket">]</span></a></sup> These so-called databases are created by various research laboratories around the world. Some of them have become de facto standards, including several public-domain subjective picture quality databases created and maintained by the <a rel="nofollow" class="external text" href="http://live.ece.utexas.edu/research/quality/">Laboratory for Image and Video Engineering (LIVE)</a> as well the <a rel="nofollow" class="external text" href="http://www.ponomarenko.info/tid2008.htm">Tampere Image Database 2008</a>. A collection of databases can be found in the <a rel="nofollow" class="external text" href="http://dbq.multimediatech.cz/">QUALINET Databases</a> repository. The <a rel="nofollow" class="external text" href="https://www.cdvl.org/">Consumer Digital Video Library</a> (CDVL) hosts freely available video test sequences for model development. </p><p>Some databases also provide pre-computed metric scores to allow others to benchmark new metrics against existing ones. Examples can be seen in the table below </p> <table class="wikitable"> <caption>Examples of Video Model Benchmark Databases </caption> <tbody><tr> <th>Benchmark </th> <th>Number of videos </th> <th>Number of metrics </th> <th>Type of metrics </th></tr> <tr> <td><a rel="nofollow" class="external text" href="https://paperswithcode.com/sota/video-quality-assessment-on-live-vqc">LIVE-VQC</a> </td> <td>585 </td> <td>11 </td> <td>No-reference </td></tr> <tr> <td><a rel="nofollow" class="external text" href="https://paperswithcode.com/sota/video-quality-assessment-on-konvid-1k">KoNViD-1k</a> </td> <td>1,200 </td> <td>11 </td> <td>No-reference </td></tr> <tr> <td><a rel="nofollow" class="external text" href="https://paperswithcode.com/sota/video-quality-assessment-on-youtube-ugc">YouTube-UGC</a> </td> <td>1,500 </td> <td>9 </td> <td>No-reference </td></tr> <tr> <td><a rel="nofollow" class="external text" href="https://videoprocessing.ai/benchmarks/no-reference-video-quality-metrics.html">MSU No-Reference VQA</a> </td> <td>2,500 </td> <td>15 </td> <td>No-reference </td></tr> <tr> <td><a rel="nofollow" class="external text" href="https://videoprocessing.ai/benchmarks/full-reference-video-quality-metrics.html">MSU Full-Reference VQA</a> </td> <td>2,500 </td> <td>44 </td> <td>Full-reference </td></tr> <tr> <td><a rel="nofollow" class="external text" href="https://github.com/baidut/PatchVQ">LIVE-FB Large-Scale Social Video Quality</a> </td> <td>39,000 </td> <td>6 </td> <td>No-reference </td></tr> <tr> <td><a rel="nofollow" class="external text" href="https://paperswithcode.com/sota/video-quality-assessment-on-live-etri">LIVE-ETRI</a> </td> <td>437 </td> <td>5 </td> <td>No-reference </td></tr> <tr> <td><a rel="nofollow" class="external text" href="https://live.ece.utexas.edu/research/LIVE_APV_Study/apv_index.html">LIVE Livestream</a> </td> <td>315 </td> <td>3 </td> <td>No-reference </td></tr></tbody></table> <p>In theory, a model can be trained on a set of data in such a way that it produces perfectly matching scores on that dataset. However, such a model will be <a href="/wiki/Overfitting" title="Overfitting">over-trained</a> and will therefore not perform well on new datasets. It is therefore advised to <a href="/wiki/Statistical_model_validation" title="Statistical model validation">validate models</a> against new data and use the resulting performance as a real indicator of the model's prediction accuracy. </p><p>To measure the performance of a model, some frequently used metrics are the <a href="/wiki/Correlation" title="Correlation">linear correlation coefficient</a>, <a href="/wiki/Spearman%27s_rank_correlation_coefficient" title="Spearman's rank correlation coefficient">Spearman's rank correlation coefficient</a>, and the <a href="/wiki/Root_mean_square_error" class="mw-redirect" title="Root mean square error">root mean square error</a> (RMSE). Other metrics are the <a href="/wiki/Kappa_statistic" class="mw-redirect" title="Kappa statistic">kappa coefficient</a> and the <a href="/wiki/Outliers_ratio" title="Outliers ratio">outliers ratio</a>. ITU-T Rec. <a rel="nofollow" class="external text" href="https://www.itu.int/rec/T-REC-P.1401-201207-I/en">P.1401</a> gives an overview of statistical procedures to evaluate and compare objective models. </p> <div class="mw-heading mw-heading3"><h3 id="Uses_and_application_of_objective_models">Uses and application of objective models</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=9" title="Edit section: Uses and application of objective models"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Objective video quality models can be used in various application areas. In <a href="/wiki/Video_codec" title="Video codec">video codec</a> development, the performance of a codec is often evaluated in terms of PSNR or SSIM. For service providers, objective models can be used for monitoring a system. For example, an <a href="/wiki/IPTV" class="mw-redirect" title="IPTV">IPTV</a> provider may choose to monitor their service quality by means of objective models, rather than asking users for their opinion, or waiting for customer complaints about bad video quality. Few of these standards have found commercial applications, including <a href="/wiki/PEVQ" class="mw-redirect" title="PEVQ">PEVQ</a> and <a href="/wiki/VQuad-HD" title="VQuad-HD">VQuad-HD</a>. <a href="/wiki/Structural_similarity" class="mw-redirect" title="Structural similarity">SSIM</a> is also part of a commercially available video quality toolset (SSIMWAVE). <a href="/wiki/Video_Multimethod_Assessment_Fusion" title="Video Multimethod Assessment Fusion">VMAF</a> is used by <a href="/wiki/Netflix" title="Netflix">Netflix</a> to tune their encoding and streaming algorithms, and to quality-control all streamed content.<sup id="cite_ref-19" class="reference"><a href="#cite_note-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-20" class="reference"><a href="#cite_note-20"><span class="cite-bracket">[</span>20<span class="cite-bracket">]</span></a></sup> It is also being used by other technology companies like <a href="/wiki/Bitmovin" title="Bitmovin">Bitmovin</a><sup id="cite_ref-21" class="reference"><a href="#cite_note-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup> and has been integrated into software such as <a href="/wiki/FFmpeg" title="FFmpeg">FFmpeg</a>. </p><p>An objective model should only be used in the context that it was developed for. For example, a model that was developed using a particular video codec is not guaranteed to be accurate for another video codec. Similarly, a model trained on tests performed on a large TV screen should not be used for evaluating the quality of a video watched on a mobile phone. </p> <div class="mw-heading mw-heading3"><h3 id="Other_approaches">Other approaches</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=10" title="Edit section: Other approaches"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>When estimating quality of a video codec, all the mentioned objective methods may require repeating post-encoding tests in order to determine the encoding parameters that satisfy a required level of visual quality, making them time consuming, complex and impractical for implementation in real commercial applications. There is ongoing research into developing novel objective evaluation methods which enable prediction of the perceived quality level of the encoded video before the actual encoding is performed.<sup id="cite_ref-22" class="reference"><a href="#cite_note-22"><span class="cite-bracket">[</span>22<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Subjective_video_quality">Subjective video quality</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=11" title="Edit section: Subjective video quality"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1236090951"><div role="note" class="hatnote navigation-not-searchable">Main article: <a href="/wiki/Subjective_video_quality" title="Subjective video quality">Subjective video quality</a></div> <p>The main goal of many-objective video quality metrics is to automatically estimate the average user's (viewer's) opinion on the quality of a video processed by a system. Procedures for <a href="/wiki/Subjective_video_quality" title="Subjective video quality">subjective video quality</a> measurements are described in <a href="/wiki/ITU-R" title="ITU-R">ITU-R</a> recommendation <a rel="nofollow" class="external text" href="http://www.itu.int/rec/R-REC-BT.500/en">BT.500</a> and ITU-T recommendation <a rel="nofollow" class="external text" href="https://www.itu.int/rec/T-REC-P.910/en">P.910</a>. In such tests, video sequences are shown to a group of viewers. The viewers' opinion is recorded and averaged into the <a href="/wiki/Mean_opinion_score" title="Mean opinion score">mean opinion score</a> to evaluate the quality of each video sequence. However, the testing procedure may vary depending on what kind of system is tested. </p> <div class="mw-heading mw-heading2"><h2 id="Tools_for_video_quality_assessment">Tools for video quality assessment</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=12" title="Edit section: Tools for video quality assessment"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1236090951"><div role="note" class="hatnote navigation-not-searchable plainlinks">This table is <a href="/wiki/Wikipedia:WikiProject_Lists#Incomplete_lists" title="Wikipedia:WikiProject Lists">incomplete</a>; you can help by <a class="external text" href="https://en.wikipedia.org/w/index.php?title=Video_quality&action=edit">expanding it</a>.</div> <table class="wikitable"> <tbody><tr> <th>Tool </th> <th>Description </th> <th>Аvailability </th> <th>License </th> <th>Included metrics </th></tr> <tr> <th><a rel="nofollow" class="external text" href="https://www.ffmpeg.org/">FFmpeg</a> </th> <td>Free and open-source multimedia tool that incorporates some video quality metrics </td> <td>Free </td> <td>Open source </td> <td>PSNR, SSIM, <a href="/wiki/Video_Multimethod_Assessment_Fusion" title="Video Multimethod Assessment Fusion">VMAF</a> </td></tr> <tr> <th><a rel="nofollow" class="external text" href="https://www.compression.ru/video/quality_measure/video_measurement_tool.html">MSU VQMT</a> </th> <td>A software suite for objective video quality assessment (full reference and no reference) </td> <td>Free for basic metrics <p>Paid for HDR metrics </p> </td> <td>Proprietary </td> <td>PSNR, SSIM, MS-SSIM, 3SSIM, <a href="/wiki/Video_Multimethod_Assessment_Fusion" title="Video Multimethod Assessment Fusion">VMAF</a>, NIQE, VQM, Delta, MSAD, MSE <p>MSU developed metrics: Blurring Metric, Blocking Metric, Brightness Flicking Metric, Drop Frame Metric, Noise Estimation Metric </p> </td></tr> <tr> <th><a rel="nofollow" class="external text" href="https://www.epfl.ch/labs/mmspg/downloads/vqmt/">EPFL VQMT</a> </th> <td>Various metrics implemented in OpenCV (C++) based on existing MATLAB implementations </td> <td>Free </td> <td>Open source </td> <td>PSNR, PSNR-HVS, PSNR-HVS-M, SSIM, MS-SSIM, VIFp </td></tr> <tr> <th><a rel="nofollow" class="external text" href="https://github.com/ballardt/openvq">OpenVQ</a> </th> <td>A toolkit implementing various metrics including the authors' OPVQ </td> <td>Free </td> <td>Open source </td> <td>PSNR, SSIM, OPVQ </td></tr> <tr> <th><a rel="nofollow" class="external text" href="https://www.elecard.com/ru/products/video-analysis/video-quality-estimator">Elecard</a> </th> <td>A commercial video quality estimation program </td> <td>Demo version available </td> <td>Proprietary </td> <td>PSNR, APSNR, MSAD, MSE, SSIM, Delta, VQM, NQI, <a href="/wiki/Video_Multimethod_Assessment_Fusion" title="Video Multimethod Assessment Fusion">VMAF</a>, VIF </td></tr> <tr> <th><a rel="nofollow" class="external text" href="http://avisynth.nl/index.php/Main_Page">AviSynth</a> </th> <td>A video processing tool that can be used as a plugin or via scription </td> <td>Free </td> <td>Open source </td> <td>SSIM </td></tr> <tr> <th><a rel="nofollow" class="external text" href="https://vicuesoft.com/vq-probe">VQ Probe</a> </th> <td>A software to calculate video quality metrics </td> <td>Free </td> <td>Proprietary </td> <td>PSNR, SSIM, <a href="/wiki/Video_Multimethod_Assessment_Fusion" title="Video Multimethod Assessment Fusion">VMAF</a> </td></tr> <tr> <th><a rel="nofollow" class="external text" href="https://vmaf.dev/">vmaf.dev</a> </th> <td>An online video quality calculation software implementing VMAF </td> <td>Free </td> <td>Open source </td> <td><a href="/wiki/Video_Multimethod_Assessment_Fusion" title="Video Multimethod Assessment Fusion">VMAF</a> </td></tr></tbody></table> <div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=13" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Glossary_of_video_terms" title="Glossary of video terms">Glossary of video terms</a></li> <li><a href="/wiki/Media_Delivery_Index" title="Media Delivery Index">MDI</a></li> <li><a href="/wiki/Mean_opinion_score" title="Mean opinion score">Mean opinion score</a></li> <li><a href="/wiki/MOVIE_Index" title="MOVIE Index">MOVIE Index</a></li> <li><a href="/wiki/Peak_signal-to-noise_ratio" title="Peak signal-to-noise ratio">PSNR</a></li> <li><a href="/wiki/Structural_similarity_index_measure" title="Structural similarity index measure">SSIM</a></li> <li><a href="/wiki/Subjective_video_quality" title="Subjective video quality">Subjective video quality</a></li> <li><a href="/wiki/Video_codecs" class="mw-redirect" title="Video codecs">Video codecs</a></li> <li><a href="/wiki/Video_Multimethod_Assessment_Fusion" title="Video Multimethod Assessment Fusion">VMAF</a></li> <li><a href="/wiki/Visual_information_fidelity" title="Visual information fidelity">Visual information fidelity</a></li></ul> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=14" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1239543626">.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist 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data-mw-deduplicate="TemplateStyles:r1238218222">.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output 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"Quantified PQoS assessment based on fast estimation of the spatial and temporal activity level". <i>Multimedia Tools and Applications</i>. <b>34</b> (3): 355–374. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2Fs11042-007-0111-1">10.1007/s11042-007-0111-1</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1380-7501">1380-7501</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:14136479">14136479</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Multimedia+Tools+and+Applications&rft.atitle=Quantified+PQoS+assessment+based+on+fast+estimation+of+the+spatial+and+temporal+activity+level&rft.volume=34&rft.issue=3&rft.pages=355-374&rft.date=2007-09-01&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A14136479%23id-name%3DS2CID&rft.issn=1380-7501&rft_id=info%3Adoi%2F10.1007%2Fs11042-007-0111-1&rft.aulast=Koumaras&rft.aufirst=H.&rft.au=Kourtis%2C+A.&rft.au=Martakos%2C+D.&rft.au=Lauterjung%2C+J.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AVideo+quality" class="Z3988"></span></span> </li> </ol></div></div> <div class="mw-heading mw-heading2"><h2 id="Further_reading">Further reading</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Video_quality&action=edit&section=15" title="Edit section: Further reading"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a rel="nofollow" class="external text" href="http://www.itu.int/rec/R-REC-BT/e">ITU-R recommendations on subjective video quality</a></li> <li><a rel="nofollow" class="external text" href="http://www.itu.int/rec/T-REC-P/e">ITU-T recommendations on objective and subjective video quality</a></li></ul>    </div><noscript><img src="https://login.wikimedia.org/wiki/Special:CentralAutoLogin/start?type=1x1" alt="" width="1" height="1" style="border: none; position: absolute;"></noscript> <div class="printfooter" data-nosnippet="">Retrieved from "<a dir="ltr" href="https://en.wikipedia.org/w/index.php?title=Video_quality&oldid=1259107991">https://en.wikipedia.org/w/index.php?title=Video_quality&oldid=1259107991</a>"</div></div> <div id="catlinks" class="catlinks" data-mw="interface"><div id="mw-normal-catlinks" class="mw-normal-catlinks"><a href="/wiki/Help:Category" title="Help:Category">Categories</a>: <ul><li><a href="/wiki/Category:Noise_(graphics)" title="Category:Noise (graphics)">Noise (graphics)</a></li><li><a href="/wiki/Category:Film_and_video_technology" title="Category:Film and video technology">Film and video technology</a></li><li><a href="/wiki/Category:Digital_television" title="Category:Digital television">Digital television</a></li><li><a href="/wiki/Category:Video_codecs" title="Category:Video codecs">Video codecs</a></li><li><a href="/wiki/Category:Codecs" title="Category:Codecs">Codecs</a></li></ul></div><div id="mw-hidden-catlinks" class="mw-hidden-catlinks mw-hidden-cats-hidden">Hidden categories: <ul><li><a href="/wiki/Category:Articles_with_short_description" title="Category:Articles with short description">Articles with short description</a></li><li><a href="/wiki/Category:Short_description_matches_Wikidata" title="Category:Short description matches Wikidata">Short description matches Wikidata</a></li><li><a href="/wiki/Category:Articles_to_be_expanded_from_July_2023" title="Category:Articles to be expanded from July 2023">Articles to be expanded from July 2023</a></li><li><a href="/wiki/Category:All_articles_to_be_expanded" title="Category:All articles to be expanded">All articles to be expanded</a></li></ul></div></div> </div> </main> </div> <div class="mw-footer-container"> <footer id="footer" class="mw-footer" > <ul id="footer-info"> <li id="footer-info-lastmod"> This page was last edited on 23 November 2024, at 11:52<span class="anonymous-show"> (UTC)</span>.</li> <li id="footer-info-copyright">Text is available under the <a href="/wiki/Wikipedia:Text_of_the_Creative_Commons_Attribution-ShareAlike_4.0_International_License" title="Wikipedia:Text of the Creative Commons Attribution-ShareAlike 4.0 International License">Creative Commons Attribution-ShareAlike 4.0 License</a>; additional terms may apply. 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