UM
Wavelet image coding based on significance extraction using morphological operation
Zhong J.M.1; Leung C.H.1; Tang Y.Y.2
1998
Source Publication5th Asia-Pacific Conference Communications and 4th Optoloelectronics Communications Conference: The Conference-Vitality to New Century, APCC/OECC 1999
Volume2
Pages900-903
AbstractIn this paper, an efficient embedded image compression algorithm is presented. It is based on the observation that the distribution of significant coefficients is intra-subband clustered and inter-subband self-similar. Morphological dilation is used to capture the clustered significant coefficients in each subband, resulting in the partitioning of each subband into significance clusters and insignificance space. Thus for entropy coding, different probability models are used for different regions according to their own probability distributions. When encoding the insignificant space, which contains mostly zeros, investigation reveals that the zerotree data structure is not very efficient to represent zeros across scales for texture images and a more efficient method is presented. Experimental results show that the proposed algorithm is very effective especially for texture images.
DOI10.1109/APCC.1999.820408
URLView the original
Language英語
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.The University of Hong Kong
2.Hong Kong Baptist University
Recommended Citation
GB/T 7714
Zhong J.M.,Leung C.H.,Tang Y.Y.. Wavelet image coding based on significance extraction using morphological operation[C],1998:900-903.
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