DocumentCode :
3487126
Title :
Sparsity-based deartifacting filtering in video compression
Author :
Xu, Jun ; Zheng, Yunfei ; Yin, Peng ; Sole, Joel ; Gomila, Cristina ; Wu, Dapeng
Author_Institution :
Thomson Corp. Res., Princeton, NJ, USA
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
3933
Lastpage :
3936
Abstract :
In the last years, many sparsity based denoising approaches for image/video denoising have been proposed. Most of them exploit the image/video sparsity model under certain over-complete basis. In this paper, we unify three sparsity-based denoising techniques and apply them to the problem of video compression artifacts removal. We compare and analyze the three techniques from the aspects of operation atom, transform dimensionality, and quantization impact. Based on the provided analysis, the paper may serve as a guideline to apply sparsity-based denoising techniques to related problems.
Keywords :
data compression; filtering theory; image denoising; video coding; operation atom; quantization impact; sparsity based denoising approach; sparsity-based deartifacting filtering; transform dimensionality; video compression; Automatic voltage control; Clustering algorithms; Filtering; Guidelines; Iterative algorithms; Noise reduction; Quantization; Video coding; Video compression; Video sequences; H.264/AVC; Video compression; artifacts removal; deblocking filtering; sparsity-based denoising;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5414030
Filename :
5414030
Link To Document :
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