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Proceedings Paper

Residual VQ (vector quantizaton) with state prediction: a new method for image coding
Author(s): Faouzi Kossentini; Mark J. T. Smith; Christopher F. Barnes
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Paper Abstract

This paper reports on a current investigation of a new approach to vector quantization (VQ) for image coding. The approach consists of integrating finite state vector quantization (FSVQ) into a binary residual vector quantizer structure. Due to the inherently predictive nature of FSVQ, the quality of image representation is often greatly superior to that of memoryless VQ (for small vector sizes). However, the codebook storage requirements are typically very large by comparison. The objective of this work is to reduce the codebook storage requirement of FSVQ without significantly impairing the reproduction quality of the coded image. Experimental results indicate that low bit rate systems based on a combination of FSVQ and RVQ can be designed with performance approaching the quality of the FSVQ schemes but with only a very small fraction of the storage requirement.

Paper Details

Date Published: 1 June 1991
PDF: 12 pages
Proc. SPIE 1452, Image Processing Algorithms and Techniques II, (1 June 1991); doi: 10.1117/12.45398
Show Author Affiliations
Faouzi Kossentini, Georgia Institute of Technology (United States)
Mark J. T. Smith, Georgia Institute of Technology (United States)
Christopher F. Barnes, Georgia Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1452:
Image Processing Algorithms and Techniques II
Mehmet Reha Civanlar; Sanjit K. Mitra; Robert J. Moorhead II, Editor(s)

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