Share Email Print

Proceedings Paper

DCT quantization matrices visually optimized for individual images
Author(s): Andrew B. Watson
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Several image compression standards (JPEG, MPEG, H.261) are based on the Discrete Cosine Transform (DCT). These standards do not specify the actual DCT quantization matrix. Ahumada & Peterson and Peterson, Ahumada & Watson provide mathematical formulae to compute a perceptually lossless quantization matrix. Here I show how to compute a matrix that is optimized for a particular image. The method treats each DCT coefficient as an approximation to the local response of a visual `channel.' For a given quantization matrix, the DCT quantization errors are adjusted by contrast sensitivity, light adaptation, and contrast masking, and are pooled non-linearly over the blocks of the image. This yields an 8 X 8 `perceptual error matrix.' A second non-linear pooling over the perceptual error matrix yields total perceptual error. With this model we may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Paper Details

Date Published: 8 September 1993
PDF: 15 pages
Proc. SPIE 1913, Human Vision, Visual Processing, and Digital Display IV, (8 September 1993); doi: 10.1117/12.152694
Show Author Affiliations
Andrew B. Watson, NASA Ames Research Ctr. (United States)

Published in SPIE Proceedings Vol. 1913:
Human Vision, Visual Processing, and Digital Display IV
Jan P. Allebach; Bernice E. Rogowitz, Editor(s)

© SPIE. Terms of Use
Back to Top