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We propose a novel lossless and lossy compression scheme for color filterarray~(CFA) sampled images based on the wavelet transform of them. Our analysissuggests that the wavelet coefficients of HL and LH subbands are highlycorrelated. Hence, we decorrelate Mallat wavelet packet decomposition tofurther sparsify the coefficients. In addition, we develop a camera processingpipeline for compressing CFA sampled images aimed at maximizing the quality ofthe color images constructed from the compressed CFA sampled images. Wevalidated our theoretical analysis and the performance of the proposedcompression scheme using images of natural scenes captured in a raw format. Theexperimental results verify that our proposed method improves coding efficiencyrelative to the standard and the state-of-the-art compression schemes CFAsampled images.

Camera-Aware Multi-Resolution Analysis (CAMRA) for Raw Sensor Data Compression