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Proceedings Paper

Image vector quantization with block-adaptive scalar prediction
Author(s): Smita Gupta; Allen Gersho
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Paper Abstract

A novel method for block coding of images is presented which combines 2-D scalar prediction with vector quantization. The input image is divided into spatially contiguous, non-overlapping square blocks and the inherent spatial nonstationarity is modeled by adaptation of the scalar predictor to each block. A new technique for the quantization of predictor coefficients is introduced which ensures the stability of the resultant inverse prediction error filter. Simulation results show that the predictor adaptation method leads to significantly improved performance compared to a coder with a fixed predictor for a nominal increase in the overall bit rate. When compared with predictive vector quantization, our coder provides higher coding gain and better perceptual quality.

Paper Details

Date Published: 1 November 1991
PDF: 11 pages
Proc. SPIE 1605, Visual Communications and Image Processing '91: Visual Communication, (1 November 1991); doi: 10.1117/12.50242
Show Author Affiliations
Smita Gupta, Univ. of California/Santa Barbara (United States)
Allen Gersho, Univ. of California/Santa Barbara (United States)


Published in SPIE Proceedings Vol. 1605:
Visual Communications and Image Processing '91: Visual Communication
Kou-Hu Tzou; Toshio Koga, Editor(s)

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