Shift-And-Decorrelate Lifting: CAMRA for Lossless Intra Frame CFA Video Compression
Yeejin Lee, Keigo Hirakawa · IEEE Signal Processing Letters · 2020
In this letter, we improve lossless intra-frame compression of color filter array (CFA) video based on Camera-Aware Multi-Resolution Analysis (CAMRA). CAMRA-based compression leverages the correlation between LH and HL subbands of wavelet-transformed CFA video frames. The key contribution of this letter is an analysis showing that the chrominance components shared by LH and HL subbands of LeGall 5/3 wavelet transform are misaligned, negatively impacting the coding efficiency. To decorrelate the subbands more effectively with minimal dynamic range growth, we developed a new lifting scheme that corrects for this misalignment. We validated our theoretical analysis and the performance of the proposed compression scheme using videos of natural scenes captured in a raw format. The experimental results verify that our proposed transform improves the coding efficiency of CFA intra-frame lossless compression.