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

Huynh Van Luong; Xin Huang; Søren Forchhammer

doi:10.1109/MMSP.2011.6093774

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

Huynh Van Luong, Xin Huang, Søren Forchhammer

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

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 language	English
Title of host publication	Proceedings of MMSP 2011
Publisher	IEEE
Publication date	2011
ISBN (Print)	978-1-4577-1434-4
DOIs	https://doi.org/10.1109/MMSP.2011.6093774
Publication status	Published - 2011
Event	13th International Workshop on Multimedia Signal Processing - Hangzhou, China Duration: 17 Oct 2011 → 19 Oct 2011 Conference number: 13 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6082085

Workshop

Workshop	13th International Workshop on Multimedia Signal Processing
Number	13
Country	China
City	Hangzhou
Period	17/10/2011 → 19/10/2011
Internet address	http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6082085

Access to Document

10.1109/MMSP.2011.6093774

http://www.mmsp2011.org/

Cite this

@inproceedings{6f791ef07a8c4e01b8bbe6d09385f6a9,

title = "Adaptive Noise Model for Transform Domain Wyner-Ziv Video using Clustering of DCT Blocks",

abstract = "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 Bj{\o}ntegaard metric) compared to the DISCOVER TDWZ video codec.",

author = "Luong, {Huynh Van} and Xin Huang and S{\o}ren Forchhammer",

year = "2011",

doi = "10.1109/MMSP.2011.6093774",

language = "English",

isbn = "978-1-4577-1434-4",

booktitle = "Proceedings of MMSP 2011",

publisher = "IEEE",

address = "United States",

note = "13th International Workshop on Multimedia Signal Processing, MMSP ; Conference date: 17-10-2011 Through 19-10-2011",

url = "http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6082085",

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AU - Huang, Xin

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PY - 2011

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N2 - 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.

AB - 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.

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