Improved distance coding of binary images by run length coding of the most probable interval

We proposed a new method to improve our previous work on efficient distance-coding of binary images, where we compressed a binary image by applying the bzip2 lossless data compressor on a sequence of intervals, which represent the distances between identical source symbols - either zeros or ones for binary images. Motivated by the observation that a majority of intervals tends to be one, we propose to run-length code this most probable interval independently from the rest of the intervals. Separate Huffman coding tables were used to code the run-lengths of the most probable interval versus other intervals. Consequently, this hybrid coding scheme allows a fraction of one bit to be assigned to the most probable interval on average, as opposed to at least one bit per interval without run-length coding, thereby contributing to about 17% improvement on the compression ratios on some test images.