Image compression using sparse colour sampling combined with nonlinear image processing

We apply two recent non-linear, image-processing algorithms to colour image compression. The two algorithms are colorization and joint bilateral filtering. Neither algorithm was designed for image compression. Our investigations were to ascertain whether their mechanisms could be used to improve the image compression rate for the same level of visual quality. Both show interesting behaviour, with the second showing a visible improvement in visual quality, over JPEG, at the same compression rate. In both cases, we store luminance as a standard, lossily compressed, greyscale image and store colour at a very low sampling rate. Each of the non-linear algorithms then uses the information from the luminance channel to determine how to propagate the colour information appropriately to reconstruct a full colour image.