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
Context-Based Lossless Compression of Mosaic Image with Bayer Pattern
2008 Congress on Image and Signal Processing ; 1 ; 481-485
2008-05-01
442338 byte
Conference paper
Electronic Resource
English
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