Error-diffused image compression using a binary-to-gray-scale decoder and predictive pruned tree-structured vector quantization

摘要

The authors consider data compression of binary error diffused images. The original contribution is using nonlinear filters to decode error-diffused images to compress them in the gray-scale domain; this gives better image quality than directly compressing the binary images. Their method is of low computational complexity and can work with any halftoning algorithm.