Share Email Print

Proceedings Paper

On transform coding tools under development for VP10
Author(s): Sarah Parker; Yue Chen; Jingning Han; Zoe Liu; Debargha Mukherjee; Hui Su; Yongzhe Wang; Jim Bankoski; Shunyao Li
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 14 October 2016
PDF: 10 pages
Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 997119 (14 October 2016); doi: 10.1117/12.2239105
Show Author Affiliations
Sarah Parker, Google, Inc. (United States)
Yue Chen, Google, Inc. (United States)
Jingning Han, Google, Inc. (United States)
Zoe Liu, Google, Inc. (United States)
Debargha Mukherjee, Google, Inc. (United States)
Hui Su, Google, Inc. (United States)
Yongzhe Wang, Google, Inc. (United States)
Jim Bankoski, Google, Inc. (United States)
Shunyao Li, Univ. of California, Santa Barbara (United States)

Published in SPIE Proceedings Vol. 9971:
Applications of Digital Image Processing XXXIX
Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top