关键词: 图像压缩, Contourlet变换, 子带内相关性, 预测算法, 多目标约束优化

Abstract: An image compression algorithm based on the dependencies between the Contourlet coefficients is proposed. Through the mutual information computation, it is discovered that strong dependencies exist in local intra-band micro-neighborhoods, and that the shape of these neighborhoods is highly anisotropic in the different decomposition bands. So the local intra-band micro-neighborhoods are used to predict the  current coefficient and the multi-objective restraint optimization method is introduced to obtain the predictor weight value. The prediction precision is enhanced effectively by the method. This algorithm is exploited in a Contourlet-based image coding application and it is showed that the decoded image has better detail and the textural property than JPEG2000 under certain compression ratio situation.

Key words: image compression, Contourlet transform, dependency in intra-band, prediction method, multi-objective restraint optimization method