Lossless and Near Lossless Compression of Real Color Filter Array data

Compression of Bayer pattern color filter array (CFA) data has gained a lot of attention during past years. Numerous algorithms have been proposed for lossless, near-lossless and lossy compression. The performance evaluation of compression methods is typically done only for artificial CFA data, obtained by sub-sampling full color images according to CFA pattern, without taking into account that CFA data are heavily processed before obtaining full color images. Therefore, some assumptions that are true for reconstructed images may not hold for real raw data. Thus, compression efficiency of different methods may vary. In this paper we evaluate the performance of some methods for lossless and near-lossless compression for real raw Bayer pattern CFA data obtained from digital cameras.


Karen Eguiazarian, co-author: Andriy Bazhyna (NVIDIA)

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