A near-lossless trellis-searched predictive image compression system

This paper presents a near-lossless image compression system where the coded image is within some prespecified maximum error of the original image at each and every pixel. The system is predictive and codes the image one row at a time. The encoder uses the Viterbi algorithm to choose among all admissible reproductions for the given image row the one that can be described with the fewest number of bits. In this paper we present a version of the system which employs run-length and Huffman coding to describe the reproductions for an image row. In addition, the system uses context modeling to further reduce the bit rate. Experimental results are presented showing the performance of the system on the large set of images provided by the ISO/IEC ITC Standards Committee.