Quantization distortion in block transform-compressed data

Abstract

Summary form only given, as follows. The JPEG image compression standard is an example of a block transform-based compression scheme; the image is systematically subdivided into blocks that are individually transformed, quantized, and encoded. The compression is achieved by quantizing the transformed data, reducing the data entropy and thus facilitating efficient encoding. Block transform compression schemes exhibit sharp discontinuities at data block boundaries: this phenomenon is a visible manifestation of the compression quantization distortion. For example, in compression algorithms such as JPEG these blocking effects manifest themselves visually as discontinuities between adjacent 8×8 pixel image blocks. In general the distortion characteristics of block transform-based compression techniques are understandable in terms of the properties of the transform basis functions and the transform coefficient quantization error. In particular, the blocking effects exhibited by JPEG are explained by two simple observations demonstrated in this work: a disproportionate fraction of the total quantization error accumulates on block edge pixels; and the quantization errors among pixels within a compression block are highly correlated, while the quantization errors between pixels in separate blocks are uncorrelated. A generic model of block transform compression quantization noise is introduced, applied to synthesized and real one and two dimensional data using the DCT as the transform basis, and results of the model are shown to predict distortion patterns observed in data compressed with JPEG.