Camera-Aware Multi-Resolution Analysis for Raw Image Sensor Data Compression
We propose novel lossless and lossy compression schemes for color filter array (CFA) sampled images based on the <underline>C</underline>amera-<underline>A</underline>ware <underline>M</underline>ulti-<underline>R</underline>esolution <underline>A</underline>nalysis, or CAMRA. Specifically, by CAMRA we refer to modifications that we make to wavelet transform of CFA sampled images in order to achieve a very high degree of decorrelation at the finest scale wavelet coefficients; and a series of color processing steps applied to the coarse scale wavelet coefficients, aimed at limiting the propagation of lossy compression errors through the subsequent camera processing pipeline. We validated our theoretical analysis and the performance of the proposed compression schemes using the images of natural scenes captured in a raw format. The experimental results verify that our proposed methods improve coding efficiency relative to the standard and the state-of-the-art compression schemes for CFA sampled images.