JPEG XR optimization with graph-based soft decision quantization

JPEG XR is the latest image compression standard. In this paper, two graph-based soft decision quantization (SDQ) methods are developed to optimize the rate-distortion performance of JPEG XR. The first approach uses a full graph, whose number of states is determined by the block size. The second method employs a fast and adaptive event-based graph, where the number of states depends on the number of nonzero indices in a normalized block, which is usually much less than the block size. Experimental results show that the fast method performs as good as the full graph method, and both methods can achieve up to 0.5 dB gain over JPEG XR.