Block-predictive image coder of neural network in multiresolution domain
Shengqiang Lou, HuangPu Ku, Liangzhu Zhou, Jiangwei Wang, Guangming Xu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
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.