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Proceedings Paper

Two Approaches To Transform Coding Using Classified Vector Quantization
Author(s): G. Tu; L. Van Eycken; A. Oosterlinck
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Paper Abstract

In this paper, two approaches of classified transform coding using vector quantization are presented and discussed. The image data, which are known to be statistically uncertain, are classified before any further quantization and coding operations. The local image activities can be ascertained either by using the neighboring decoded data e. finite-state method) or by examining the current data (i. e. activity-detection method). The finite-state method, which is more preferable to he implemented using small transform blocks (typically 4 x 4) due to the fact that the inter-block correlations decrease for larger block dimensions, provides satisfied data classifications without requiring extra indication bits. The activity-detection method is however more likely to have larger transform blocks in order to keep the number of the extra indication bits at a reasonable level. Other practical considerations for both methods are also given.

Paper Details

Date Published: 1 November 1989
PDF: 8 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970067
Show Author Affiliations
G. Tu, Catholic University of Leuven (Belgium)
L. Van Eycken, Catholic University of Leuven (Belgium)
A. Oosterlinck, Catholic University of Leuven (Belgium)


Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)

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