TREE CODING OF BILEVEL IMAGES

Presently, sequential tree coders are the best general purpose bilevel image coders and the best coders of halftoned images? The current ISO standard, Joint Bilevel Image Experts Group (JBIG), is a good example , A sequential tree coder encodes the data by feeding estimates of con ditional probabilities to an arithmetic coder, The conditional probabi lities are estimated from co-occurrence statistics of past pixels, the statistics are stored in a tree, By organizing code length calculatio ns properly, a vast number of possible models (trees) reflecting diffe rent pixel orderings can be investigated within reasonable time prior to generating the code, A number of general-purpose coders are constru cted according to this principle, Rissanen's one-p:lss algorithm, cont ext, is presented in two modified versions, The baseline is proven to be a universal coder, The faster version, which is one order of magnit ude slower than JBIG, obtains excellent and highly robust compression performance, A multipass free tree coding scheme produces superior com pression results for all test images, A multipass free template coding scheme produces significantly better results than JBIG for difficult images such as halftones, By utilizing randomized subsampling in the t emplate selection, the speed becomes acceptable for practical image co ding.