A Binary Image Scalable Coder Based on Reversible Cellular Automata Transform and Arithmetic Coding

In this work, we have designed an efficient arithmetic coder for the non-linear bi-level image coder based on reversible cellular automata transform reported in the work of Cruz-Reyes and Kari (2008). The proposed approach relies on non-linear transform operations based on RmbCA, decomposing the image into four subimages (named LL, LH, HL, HH in lexicographic order) in such a way that the LL subimage represents a low resolution version of the original image. Performing an edge detection on this subimage, it is possible to identify the coordinates where there is a high probability that the other subimages present a black pixels. In this way it is possible to minimize the amount of data that have to be processed reducing the coded bit stream. In order to increase the probability that black pixels lie in the selected region, the coding algorithm enlarges the identified region according to the values of Sobel operators computed on the LL subimage.