“High Speed Lossless Compression Method for Color Still Images”

In case that we separate RGB color still images into R-, G- and B- color planes, it is known that the color plane images have highly correlation each other. It is also known that the images have different properties in a locally called context. In this paper, we propose lossless compression method for RGB color still images which is realized by removing these redundancies. In the proposed method, we generate color difference component of the prediction errors obtained from predictive transformation on each plane. Then we separate the prediction errors and the color differences of the prediction errors according to their context, and apply optimal entropy coding for each context. From the simulation results, we confirmed that the compression of the proposed method improved by 14% and by 13% in comparison with that of the LOCO-I and that of the CALIC, respectively, and was also equivalent to that of the CREW. And we also confirmed that the processing time of the proposed method was faster than that of these conventional methods.