Adaptive Noise Model for Transform Domain Wyner-Ziv Video using Clustering of DCT Blocks

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2011

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The noise model is one of the most important aspects influencing the coding performance of Distributed Video Coding. This paper proposes a novel noise model for Transform Domain Wyner-Ziv (TDWZ) video coding by using clustering of DCT blocks. The clustering algorithm takes advantage of the residual information of all frequency bands, iteratively classifies blocks into different categories and estimates the noise parameter in each category. The experimental results show that the coding performance of the proposed cluster level noise model is competitive with state-ofthe- art coefficient level noise modelling. Furthermore, the proposed cluster level noise model is adaptively combined with a coefficient level noise model in this paper to robustly improve coding performance of TDWZ video codec up to 1.24 dB (by Bjøntegaard metric) compared to the DISCOVER TDWZ video codec.
Original languageEnglish
TitleProceedings of MMSP 2011
PublisherIEEE
Publication date2011
ISBN (print)978-1-4577-1434-4
DOIs
StatePublished

Workshop

Workshop13th International Workshop on Multimedia Signal Processing
Number13
CountryChina
CityHangzhou
Period17-10-1119-10-11
Internet addresshttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6082085
CitationsWeb of Science® Times Cited: No match on DOI

ID: 6319314