Image compression using spatial prediction

Abstract

This paper describes a new image compression technique, referred to as spatial prediction. Spatial prediction works in a manner similar to fractal-based image compression techniques, and is in fact a result of several experiments that we conducted to gain a better understanding of why fractal compression works. Spatial prediction compresses an image by storing, for each image block, either the quantized Discrete Cosine Transform (DCT) coefficients or the parameters of an affine transformation that constructs the block using another image block from the already encoded portion of the image. This technique does not require contractivity in the affine transformations and performs as well as or better than fractal compression. Spatial prediction does not out-perform pure DCT-based techniques (such as JPEG) in terms of PSNR/bit-rate tradeoff. However, at very low bit rates it results in far fewer blocky artifacts and markedly better visual quality.