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Colour image compression by grey to colour conversion

Instead of de-correlating image luminance from chrominance, some use has been made of using the correlation between the luminance component of an image and its chromatic components, or the correlation between colour components, for colour image compression. In one approach, the Green colour channel was taken as a base, and the other colour channels or their DCT subbands were approximated as polynomial functions of the base inside image windows. This paper points out that we can do better if we introduce an addressing scheme into the image description such that similar colours are grouped together spatially. With a Luminance component base, we test several colour spaces and rearrangement schemes, including segmentation. and settle on a log-geometric-mean colour space. Along with PSNR versus bits-per-pixel, we found that spatially-keyed s-CIELAB colour error better identifies problem regions. Instead of segmentation, we found that rearranging on sorted chromatic components has almost equal performance and better compression. Here, we sort on each of the chromatic components and separately encode windows of each. The result consists of the original greyscale plane plus the polynomial coefficients of windows of rearranged chromatic values, which are then quantized. The simplicity of the method produces a fast and simple scheme for colour image and video compression, with excellent results.