Error-Diffused Image Compression Using a Binary-to-Gray-Scale Decoder and Predictive Pruned Tree-Structured Vector Quantization

This correspondence considers 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. Our method is of low computational complexity and can work with any halftoning algorithm.