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Volume: 29 | Article ID: art00013
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Adaptive multi-reference prediction using a symmetric framework
  DOI :  10.2352/ISSN.2470-1173.2017.2.VIPC-409  Published OnlineJanuary 2017
Abstract

Google started the WebM Project in 2010 to develop open source, royalty--free video codecs designed specifically for media on the Web. Subsequently, Google jointly founded a consortium of major tech companies called the Alliance for Open Media (AOM) to develop a new codec AV1, aiming at a next edition codec that achieves at least a generational improvement in coding efficiency over VP9. This paper proposes a new coding tool as one of the many efforts devoted to AOM/AV1. In particular, we propose a second ALTREF_FRAME in the AV1 syntax, which brings the total reference frames to seven on top of the work presented in [11]. ALTREF_FRAME is a constructed, no-show reference obtained through temporal filtering of a look-ahead frame. The use of twoALTREF_FRAMEs adds further flexibility to the multi-layer, multi-reference symmetric framework, and provides a great potential for the overall Rate- Distortion (RD) performance enhancement. The experimental results have been collected over several video test sets of various resolutions and characteristics both texture- and motion-wise, which demonstrate that the proposed approach achieves a consistent coding gain, compared against the AV1 baseline as well as against the results in [11]. For instance, using overall-PSNR as the distortion metric, an average bitrate saving of 5.880% in BDRate is obtained for the CIF-level resolution set, and 4.595% on average for the VGA-level resolution set.

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Zoe Liu, Debargha Mukherjee, Wei-Ting Lin, Paul Wilkins, Jingning Han, Yaowu Xu, "Adaptive multi-reference prediction using a symmetric frameworkin Proc. IS&T Int’l. Symp. on Electronic Imaging: Visual Information Processing and Communication VIII,  2017,  pp 65 - 72,  https://doi.org/10.2352/ISSN.2470-1173.2017.2.VIPC-409

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