Wyner-Ziv Video Coding using Hadamard Transform and Deep Learning
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 7
Abstract
Predictive schemes are current standards of video coding. Unfortunately they do not apply well for lightweight devices such as mobile phones. The high encoding complexity is the bottleneck of the Quality of Experience (QoE) of a video conversation between mobile phones. A considerable amount of research has been conducted towards tackling that bottleneck. Most of the schemes use the so-called Wyner-Ziv Video Coding Paradigm, with results still not comparable to those of predictive coding. This paper shows a novel approach for Wyner-Ziv video compression. It is based on the Reinforcement Learning and Hadamard Transform. Our Scheme shows very promising results.
Authors and Affiliations
Jean-Paul Kouma, Ulrik Soderstrom
Keywords
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- EP ID EP112543
- DOI 10.14569/IJACSA.2016.070779
- Views 116
- Downloads 0
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