In most digital cameras, demosaicing and compression are generally performed sequentially. Recently, it was found that compression- first schemes outperform the conventional demosaicing-first schemes in terms of image quality. An efficient lossless compression scheme for Bayer CFA images is presented in this paper. It exploits a context matching technique to rank the neighboring pixels when predicting a pixel. The prediction residue is then encoded with an adaptive coding scheme using Rice code. Simulation results show that the proposed algorithm can achieve a better compression performance as compared with conventional lossless CFA image coding methods.
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