Finite Ridgelet Transform Based Listless Block-Partitioning Image Coding Algorithm

In this paper, an image coding algorithm based on a rate-distortion optimized orthonormal finite ridge let transform (OFRIT) decomposition and on an improved listless block-partitioning coding scheme which quantizes each sub band separately is proposed. The ridge let transform can provide optimally sparse representation of objects with singularities along straight edges and the orthonormal finite ridge let transform(OFRIT) can decompose the high frequency parts of the images. A linear indexing technique is used to rep resent the coordinate of a coefficient with a single number instead of two for computational efficiency and algorithm simplicity. Instead of lists, a state table with four bits per coefficient keep s track of the significance of the set and pixel. Each sub band is encoded by a quad tree 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 outperforms SPIHT and JPEG2000 schemes in novel image with straight lines significantly or curve lines significantly coding in terms of both PSNR and visual quality, it has a fixed predetermined memory requirement of about 50% of the image size.