Block-predictive image coder of neural network in multiresolution domain

ShengQiang Lou; HuangPu Ku; Liangzhu Zhou; Jiangwei Wang; Guangming Xu

doi:10.1117/12.269780

1 April 1997 Block-predictive image coder of neural network in multiresolution domain

ShengQiang Lou, HuangPu Ku, Liangzhu Zhou, Jiangwei Wang, Guangming Xu

Proceedings Volume 3030, Applications of Artificial Neural Networks in Image Processing II; (1997) https://doi.org/10.1117/12.269780
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

Abstract

The redundancy of the multiresolution representation has been clearly demonstrated in the case of fractal images, but has not been fully recognized and exploited for general images. This paper presents a new image coder in which the similarity among blocks of different subbands is exploited by block prediction based on neural network. After a pyramid subband decomposition, the detail subbands are partitioned into a set of uniform non-overlapping blocks. In order to speed up the coding procedure and improve the coding efficiency, a new classifying criteria is presented, the blocks are classified into two sets: the simple block set and the edge block set. In our proposed method, the edge blocks are predicted from blocks in lower scale subband with same orientation through neural network. The simple blocks and predictive edge error blocks are coded with an arithmetic coder. Simulation results show that the method presented in this paper is a promising coding technique which is worth further research.

Citation Download Citation

ShengQiang Lou, HuangPu Ku, Liangzhu Zhou, Jiangwei Wang, and Guangming Xu "Block-predictive image coder of neural network in multiresolution domain", Proc. SPIE 3030, Applications of Artificial Neural Networks in Image Processing II, (1 April 1997); https://doi.org/10.1117/12.269780

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