Segmentation-based lossless compression for color images

It is generally accepted that a color image may be encoded by using a gray-scale compression technique on each of the three-color planes. Such an approach, however, does not take advantage of the correlation existing between the color planes. In this paper, a new segmentation-based lossless compression method is proposed for color images. The method exploits the correlation existing among the three-color planes by treating each pixel as a vector of three components, and performing region growing and difference operations using the vectors. The method performed better than the Joint Photographic Experts Group (JPEG) standard by an average of 0.68 bit/pixel with a database including four natural color images of scenery, four images of burn wounds, and four fractal images. A transformation from the RGB planes to the luminance, in-phase, and quadrature-phase (YIQ) planes is applied, obtaining much better compression efficiency, given by 2.42 b/pixel over JPEG