Novel scheme for low-power classified vector quantisation image coding

A novel scheme for low-power image decoding based on classified vector is p resented. The main idea is the of the memory accesses to large memories (mo st power-consuming by arithmetic and/or application specific computations. Specifically, the proposed image coding scheme uses small sub-codebooks to reduce the memory requirements and memory-related power consumption in comp arison with classical vector quantisation schemes. By applying simple trans formations on the codewords during coding, the proposed scheme extends the small sub-codebooks, compensating for the quality degradation introduced by their small size. Thus, the main coding task becomes computation-based rat her than memory-based, leading to a significant reduction in power consumpt ion. A coding and quantisation replacement background operations), proposed comparable traditional parameters of the transformations depend on the ima ge block under coding, and the small subcodebooks are dynamically adapted e ach time to this specific image block. The main disadvantage of the propose d scheme is the decrease in the compression ratio in comparison with classi cal vector quantisation. A joint (quality-compression ratio) optimisation p rocedure is used to keep this side-effect as small as possible.