Multi-directional implicit weighted prediction based on image characteristics of reference pictures for inter coding
Weighted prediction (WP) in H.264/MPEG-4 AVC (H.264) is an efficient motion compensation technique to predict illumination variation and consists of two modes: an explicit WP (EWP) and an implicit WP (IWP). Since in IWP, only weighting factors are implicitly derived from reference pictures used for...
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description | Weighted prediction (WP) in H.264/MPEG-4 AVC (H.264) is an efficient motion compensation technique to predict illumination variation and consists of two modes: an explicit WP (EWP) and an implicit WP (IWP). Since in IWP, only weighting factors are implicitly derived from reference pictures used for bi-prediction, and the offsets are always set to 0, there are issues in that IWP cannot utilize the optimal WP parameters, and cannot be applied to uni-prediction. In order to overcome these issues, this paper presents a novel decoding process to derive WP parameters implicitly by using the Multi-Directional Implicit Weighted Prediction (MD-IWP) method. WP parameters are derived using the image characteristics of reference pictures. By linearly predicting the image characteristics of the target picture using different reference pictures stored in the decoded picture buffer, WP parameters of uni-prediction can also be derived. This method can achieve 15% to 50% bitrate reduction compared to the conventional IWP method. This gain is almost the same or better than in the case of EWP with the simple 1-pass parameter estimation method. |
doi_str_mv | 10.1109/ICIP.2012.6467167 |
format | Conference Proceeding |
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Since in IWP, only weighting factors are implicitly derived from reference pictures used for bi-prediction, and the offsets are always set to 0, there are issues in that IWP cannot utilize the optimal WP parameters, and cannot be applied to uni-prediction. In order to overcome these issues, this paper presents a novel decoding process to derive WP parameters implicitly by using the Multi-Directional Implicit Weighted Prediction (MD-IWP) method. WP parameters are derived using the image characteristics of reference pictures. By linearly predicting the image characteristics of the target picture using different reference pictures stored in the decoded picture buffer, WP parameters of uni-prediction can also be derived. This method can achieve 15% to 50% bitrate reduction compared to the conventional IWP method. 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This gain is almost the same or better than in the case of EWP with the simple 1-pass parameter estimation method.</description><subject>Correlation</subject><subject>Decoding</subject><subject>Encoding</subject><subject>Equations</subject><subject>HEVC</subject><subject>Implicit mode</subject><subject>Mathematical model</subject><subject>Motion compensation</subject><subject>Parameter estimation</subject><subject>Video coding</subject><subject>Weighted prediction</subject><issn>1522-4880</issn><issn>2381-8549</issn><isbn>1467325341</isbn><isbn>9781467325349</isbn><isbn>9781467325332</isbn><isbn>1467325325</isbn><isbn>9781467325325</isbn><isbn>1467325333</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kMtOAzEMRcNLoi39AMQmPzAlmWTyWKKKR6UiWMC6yiROazSdqTJBiL8ngrKyfa99ZR1CrjlbcM7s7Wq5el3UjNcLJZXmSp-QudWGl0HUjRD1KZnUwvDKNNKekem_Ifk5mfCmritpDLsk03H8YKwECT4h-fmzy1gFTOAzDr3rKO4PHXrM9Atwu8sQ6CFBwF-btm4sQmlw77ZA_c4l5zMkHDP6kQ6RJoiQoPdAD-XmM8FI45Ao9mWL-iFgv70iF9F1I8yPdUbeH-7flk_V-uVxtbxbV8h1kyvVWh1DNExrFwWzWrXKypZzG0SrlfVG82jaRirXGlVIhCBdY4KPQTasEJmRm79cBIDNIZWf0_fmSE_8AHwGYYQ</recordid><startdate>201209</startdate><enddate>201209</enddate><creator>Tanizawa, Akiyuki</creator><creator>Chujoh, T.</creator><creator>Yamakage, T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201209</creationdate><title>Multi-directional implicit weighted prediction based on image characteristics of reference pictures for inter coding</title><author>Tanizawa, Akiyuki ; Chujoh, T. ; Yamakage, T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-6b97fdf8077af30976b694b119d3b769c871f8b546ab86781dd4a58dcfd450533</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Correlation</topic><topic>Decoding</topic><topic>Encoding</topic><topic>Equations</topic><topic>HEVC</topic><topic>Implicit mode</topic><topic>Mathematical model</topic><topic>Motion compensation</topic><topic>Parameter estimation</topic><topic>Video coding</topic><topic>Weighted prediction</topic><toplevel>online_resources</toplevel><creatorcontrib>Tanizawa, Akiyuki</creatorcontrib><creatorcontrib>Chujoh, T.</creatorcontrib><creatorcontrib>Yamakage, T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tanizawa, Akiyuki</au><au>Chujoh, T.</au><au>Yamakage, T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Multi-directional implicit weighted prediction based on image characteristics of reference pictures for inter coding</atitle><btitle>2012 19th IEEE International Conference on Image Processing</btitle><stitle>ICIP</stitle><date>2012-09</date><risdate>2012</risdate><spage>1545</spage><epage>1548</epage><pages>1545-1548</pages><issn>1522-4880</issn><eissn>2381-8549</eissn><isbn>1467325341</isbn><isbn>9781467325349</isbn><eisbn>9781467325332</eisbn><eisbn>1467325325</eisbn><eisbn>9781467325325</eisbn><eisbn>1467325333</eisbn><abstract>Weighted prediction (WP) in H.264/MPEG-4 AVC (H.264) is an efficient motion compensation technique to predict illumination variation and consists of two modes: an explicit WP (EWP) and an implicit WP (IWP). Since in IWP, only weighting factors are implicitly derived from reference pictures used for bi-prediction, and the offsets are always set to 0, there are issues in that IWP cannot utilize the optimal WP parameters, and cannot be applied to uni-prediction. In order to overcome these issues, this paper presents a novel decoding process to derive WP parameters implicitly by using the Multi-Directional Implicit Weighted Prediction (MD-IWP) method. WP parameters are derived using the image characteristics of reference pictures. By linearly predicting the image characteristics of the target picture using different reference pictures stored in the decoded picture buffer, WP parameters of uni-prediction can also be derived. This method can achieve 15% to 50% bitrate reduction compared to the conventional IWP method. 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subjects | Correlation Decoding Encoding Equations HEVC Implicit mode Mathematical model Motion compensation Parameter estimation Video coding Weighted prediction |
title | Multi-directional implicit weighted prediction based on image characteristics of reference pictures for inter coding |
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