  We propose a novel lossless and lossy compression scheme for color filter
array~(CFA) sampled images based on the wavelet transform of them. Our analysis
suggests that the wavelet coefficients of HL and LH subbands are highly
correlated. Hence, we decorrelate Mallat wavelet packet decomposition to
further sparsify the coefficients. In addition, we develop a camera processing
pipeline for compressing CFA sampled images aimed at maximizing the quality of
the color images constructed from the compressed CFA sampled images. We
validated our theoretical analysis and the performance of the proposed
compression scheme using images of natural scenes captured in a raw format. The
experimental results verify that our proposed method improves coding efficiency
relative to the standard and the state-of-the-art compression schemes CFA
sampled images.
