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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    Titel :

    Context-Based Lossless Compression of Mosaic Image with Bayer Pattern


    Beteiligte:
    Cheng, Yongqiang (Autor:in) / Xie, Keming (Autor:in) / Zhang, Gang (Autor:in)


    Erscheinungsdatum :

    01.05.2008


    Format / Umfang :

    442338 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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