Lossless compression of Bayer pattern color filter arrays
Andriy V. Bazhyna, Atanas P. Gotchev, Karen Egiazarian · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
In this contribution, we study the problem of lossless compression of Bayer pattern CFA data. Two main issues are addressed: how to pack (reorder) pixels from the red, green and blue color planes into a structure appropriate for the subsequent compression algorithm (structural transformation) and how to utilize possible correlations between colors. While structural transformation to the red and blue color planes is straightforward as they are directly downsampled onto compact rectangular grids, the quincunx sampling grid of the green pixels allows different separations. We explore three different methods for green pixels separation and compare their peculiarities in the light of the chosen prediction-based compression algorithm, i.e. JPEG-LS. Two color decorrelation approaches are proposed as well. In the first approach, simple difference between the red or blue pixel and the corresponding nearest green pixel is calculated. In the second approach, several nearest green pixels are used to estimate the real green pixel value for the particular red or blue pixel location. The performance of the proposed algorithm is tested for real CFA raw data and results in terms of compression ratio are presented.