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Proceedings Paper

HMM based distributed arithmetic coding and its application in image coding
Author(s): Dong Wang; Lin Huang
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Paper Abstract

Distributed source coding was proved to be suitable to correlated sources environments. This paper intends to explore a new way to improve distributed arithmetic coding and apply it in image coding. The proposed method models the correlation between sources as a Hidden Markov Model process. The decoder uses Viterbi algorithm to get a better error rate. Adjacent lines of the image are regarded as correlated sources in image coding process. Experiments that compress synthetic and real image data are carried on and the result shows that Hidden Markov Model-based distributed arithmetic coding can get better code rate and lower frame error rate.

Paper Details

Date Published: 13 March 2013
PDF: 6 pages
Proc. SPIE 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing, 87831V (13 March 2013); doi: 10.1117/12.2021231
Show Author Affiliations
Dong Wang, Northwest Agriculture and Forestry Univ. (China)
Lin Huang, Northwest Agriculture and Forestry Univ. (China)


Published in SPIE Proceedings Vol. 8783:
Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)

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