A novel image compression using grey models on a dynamic window

Based on the grey model (GM), a simple and fast methodology is developed fo r lossy image compression. First of all, the image is decomposed into some different-size image windows through the judgement of grey difference level ; then the GM (1, 1) of grey system theory is used as a fitter to model tho se window pixels. The proposed algorithms can be contrasted with the conven tional compression techniques such as discrete cosine transform or vector q uantization (VQ) algorithms in their dynamic modelling sequence and flexibl e block size. Especially, the compression and decompression process do not require an extra decoder and only utilize the modelling parameters to recon struct the image by reversing the operation of GM (1, 1). Experiments with some (512 x 512) images indicate that not only the average bit number per p ixel and peak signal-to-noise ratio but also the coding time and decoding t ime of this lossy image compression algorithm based on GM (1, 1) are better than those of block truncation coding with VQ.