On the use of context-weighting in lossless bilevel image compression.

We present a context-weighting algorithm that adaptively weights in real-time three-context models based on their relative accuracy. It can automatically select the better model over different regions of an image, producing better probability estimates than using either one of these models exclusively. Combined with the previously proposed block arithmetic coder for image compression (BACIC), the overall performance is slightly better than JBIG for the eight CCITT business-type test images, outperforms JBIG by 13.