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2011 IEEE International Conference on Multimedia and Expo
Multiple component predictive coding framework of still images
Barcelona
July 11-July 15
ISBN: 978-1-61284-348-3
Xiyuan Hu, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
Weiping Xia, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
Silong Peng, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
Wen-Liang Hwang, Institute of Information Science, Academia Sinica, Taipei 11529, Taiwan, R.O.C.
In this paper, we propose a multiple component predictive coding framework. We firstly separate the reconstructed image into several subcomponents; and then predict each subcomponent independently but encode them together. To separate image into multiple subcomponents, we also propose a fast operator-based image separation algorithm. With the help of multicomponent prediction strategy, our prediction results can achieve superior performance than the H.264/AVC intra frame prediction method for images containing rich textures. By adopting the residue coding method used in H.264/AVC, we compare the compression efficacy of our proposed algorithm with the state-of-art JPEG2000 and H.264/AVC intra frame compression algorithms in the experimental part. The numerical results show that our algorithm is better than both H.264/AVC intra frame coding algorithm and JPEG2000 algorithm for images with ample textures.
Citation:
Xiyuan Hu, Weiping Xia, Silong Peng, Wen-Liang Hwang, "Multiple component predictive coding framework of still images," icme, pp.1-6, 2011 IEEE International Conference on Multimedia and Expo, 2011
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