Wavelet-based contourlet transform based listless block-partitioning image coding algorithm with rate-distortion optimization

In this paper, an image coding algorithm based on a rate-distortion optimized wavelet-based contourlet transform (WBCT) decomposition and on an improved listless block-partitioning coding scheme which quantizes each subband separately is proposed. The Wavelet-Based Contourlet Transform (WBCT) can provide optimally sparse representation of objects with singularities along c² edges. Instead of lists, a state table with four bits per coefficient keep s track of the significance of the set and pixel. Each subband is encoded by a quadtree based set partitioning process. This algorithm needs no lists and thus can avoid unfixed memory requirement and the operations of list nodes. The experimental results show that the proposed algorithm runs faster than SPIHT and JPEG2000 and set partitioning in hierarchical trees. The proposed algorithm significantly outperforms SPIHT and JPEG2000 schemes and also surpasses WBCT based image coding algorithms, it has a fixed predetermined memory requirement of about 50% of the image size.