Paper Info
Title
Evaluation of Side Information Effectiveness in Distributed Video Coding
Abstract
The rate-distortion performance of a distributed video coding system strongly depends on the characteristics of the side information. One could naïvely think that the best side information is the one with the largest PSNR with respect to the original corresponding image. However, previous works have shown that this is not always the case and a reduction of the side information MSE does not always translate into better rate-distortion performance for the complete system. The scope of this paper is to explore a set of metrics other than the PSNR and explicitly designed to classify the side information with respect to its impact on the end-to-end compression performance. A first contribution is to define an experimental framework that can be used to meaningfully compare different metrics for side information evaluation. As a second contribution, our analysis allows to understand why in some cases PSNR-based metrics provide a fairly reliable estimation of the side information quality, while in other cases they do not. This analysis also allows us to introduce a set of new metrics that are better adapted for side information effectiveness evaluation, and that are based on a suitable power of the absolute difference between side information and the original image, or on the Hamming distance between the respective transform coefficients. Besides their theoretical interest, these new metrics can also improve the rate-distortion performance of some distributed video coding systems such as the hash-based ones. We observe improvement up to 74% rate reduction in a simple study case.
Year
DOI
Venue
2013
10.1109/TCSVT.2013.2273623
Circuits and Systems for Video Technology, IEEE Transactions
Keywords
Field
DocType
estimation theory,rate distortion theory,video coding,Hamming distance,PSNR-based metrics,distributed video coding system,end-to-end compression performance,rate-distortion performance,side information MSE,side information effectiveness evaluation,side information quality,transform coefficients,Distributed video coding,quality evaluation,side information
Computer vision,Coding tree unit,Computer science,Side information,Coding (social sciences),Hamming distance,Artificial intelligence,Hash function,Estimation theory,Rate–distortion theory,Absolute difference
Journal
Volume
Issue
ISSN
23
12
1051-8215
Citations 
PageRank 
References 
4
0.40
36
Authors
4
Name
Order
Citations
PageRank
Thomas Maugey127131.16
Jérôme Gauthier2324.39
Marco Cagnazzo329434.45
Béatrice Pesquet-Popescu487691.43