Region adaptive spectral transformation for wavelet based color image compression

In general, each region of a color image exhibits different spectral characteristics. Therefore, the energy compaction characteristic of a single global spectral transformation is rather weak for compression purposes. In this paper, we propose that different groups of wavelet coefficients of a color image be subjected to different spectral transformations prior to the spectral planes being coded by a wavelet-based image coder such as CSPIHT (Color Set Partitioning in Hierarchical Trees, [7]). The decomposition of the color image into such groups is succintly represented with a quadtree structure which is optimized for rate-distortion performance by means of a known analytical rate-distortion model for wavelet-based image codecs. The experiments show that, when integrated with the CSPIHT coder, the proposed region adaptive transformation method yields compression gains of 0.4-0.5 dB, on the average, for rates between 0.5bpp and 2.5bpp over the single global transformation method.