DocumentCode
463565
Title
A Novel Scalable Texture Video Coding Scheme with GPCA
Author
Liu, Jian ; Zhuang, Yueting ; Yao, Lei ; Wu, Fei
Author_Institution
Coll. of Comput. Sci., Zhejiang Univ., Hangzhou
Volume
1
fYear
2007
fDate
15-20 April 2007
Abstract
This paper proposes a novel SNR scalable coding method with the support of generalized principle component analysis (GPCA). This method encodes the low-pass and high-pass pictures generated by the MCTF decomposition with a hybrid linear model instead of traditional block-based DCT transform. GPCA is a powerful tool to identify the hybrid linear model in the textures, which segment the texture into heterogeneous regions, and then encode each region with PCA method. By keeping various proportions of PCA coefficients, and altering the quantization step sizes for different layers, a better scalable coding result can be achieved.
Keywords
filtering theory; image texture; motion compensation; principal component analysis; video coding; GPCA; MCTF decomposition; SNR; generalized principle component analysis; high-pass pictures; hybrid linear model; low-pass pictures; motion-compensated temporal filtering; scalable texture video coding scheme; Automatic voltage control; Discrete cosine transforms; Hybrid power systems; Image coding; Principal component analysis; Scalability; Streaming media; Video coding; Video compression; Video sequences; GPCA; Video coding; hybrid linear model; scalability; texture coding;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location
Honolulu, HI
ISSN
1520-6149
Print_ISBN
1-4244-0727-3
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2007.366077
Filename
4217249
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