On transform coding tools under development for VP10

Sarah Parker; Yue Chen; Jingning Han; Zoe Liu; Debargha Mukherjee; Hui Su; Yongzhe Wang; Jim Bankoski; Shunyao Li

doi:10.1117/12.2239105

14 October 2016 On transform coding tools under development for VP10

Sarah Parker, Yue Chen, Jingning Han, Zoe Liu, Debargha Mukherjee, Hui Su, Yongzhe Wang, Jim Bankoski, Shunyao Li

Proceedings Volume 9971, Applications of Digital Image Processing XXXIX; 997119 (2016) https://doi.org/10.1117/12.2239105
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States

Abstract

Google started the WebM Project in 2010 to develop open source, royaltyfree video codecs designed specifically for media on the Web. The second generation codec released by the WebM project, VP9, is currently served by YouTube, and enjoys billions of views per day. Realizing the need for even greater compression efficiency to cope with the growing demand for video on the web, the WebM team embarked on an ambitious project to develop a next edition codec, VP10, that achieves at least a generational improvement in coding efficiency over VP9. Starting from VP9, a set of new experimental coding tools have already been added to VP10 to achieve decent coding gains. Subsequently, Google joined a consortium of major tech companies called the Alliance for Open Media to jointly develop a new codec AV1. As a result, the VP10 effort is largely expected to merge with AV1. In this paper, we focus primarily on new tools in VP10 that improve coding of the prediction residue using transform coding techniques. Specifically, we describe tools that increase the flexibility of available transforms, allowing the codec to handle a more diverse range or residue structures. Results are presented on a standard test set.

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Citation Download Citation

Sarah Parker, Yue Chen, Jingning Han, Zoe Liu, Debargha Mukherjee, Hui Su, Yongzhe Wang, Jim Bankoski, and Shunyao Li "On transform coding tools under development for VP10", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 997119 (14 October 2016); https://doi.org/10.1117/12.2239105

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