Optimizing bit-plane context-dependent entropy coding for palettized images

We present a special greedy algorithm for assigning codebook bits in order to improve the context-dependent compression of palettized images. Our method provides superior compression to that of other bit-plane compression schemes, such as a “random” method based on the palettization process itself, and binary sequence coding; the improvement is quite large for the full M-ary Markov model. Our method avoids the high computational costs of exhaustive codebook search, and can be tailored to specific context models and hardware constraints