An overview of lossless compression scheme for Bayer color filter array images
Sulbha Yadav, Vipul Dalal · 2010
TO reduce cost, most digital cameras use a single image sensor to capture color images. Bayer color filter array (CFA) images are captured and demosaicing is generally carried out before compression. Recently, it was found that a single error on the raw data may cause a spatial propagation of the error pattern depending on the CFA pattern position. Moreover, the interpolation process is time consuming and it increases the dimension of the data without increasing the information content of the original image. An alternative way to deal with CFA data is to directly compress it and perform the full color interpolation at the decoder. This paper gives the overview of an adaptive lossless compression scheme for bayer color filter array images using context matching based prediction technique. This scheme uses Context Matching Technique to predict a pixel by matching neighboring pixel, an adaptive color difference estimation scheme to remove the color spectral redundancy when handling red and blue samples and an adaptive codeword generation technique to encode the prediction residues. This method generally provides a better compression performance as compared with the existing lossless CFA image compression schemes.