In this paper, a predictive model for compression of mosaic image with Bayer pattern is proposed. It consists of TFNN neural network predictor and adaptive correction part based on context. As in JPEG-LS, the adaptive part of the predictor is context-based and it is used to “cancel” the integer part of the offset due to the TFNN predictor. In the meantime, we propose a context quantization approach that achieves high coding efficiency. Compared with existing methods of CFA image lossless compression, the performance of proposed method is apparently the best


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    Title :

    Context-Based Lossless Compression of Mosaic Image with Bayer Pattern


    Contributors:


    Publication date :

    2008-05-01


    Size :

    442338 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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