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Proceedings Paper

Quad-Tree Product Vector Quantization Of Images
Author(s): Chung-yen Chiu; Richard L. Baker
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Paper Abstract

Variable rate image coding schemes are an efficient way to achieve low bit rates while maintaining acceptable image quality. This paper describes several ways to design variable rate product vector quantizers (VQ) which use a quad-tree data structure to communicate the VQ's block size. The first is a direct encoding method which uses VQs having previously specified rates. The second uses a threshold decision rule together with a method to compute the threshold to keep average distortion below a given level. This computation is based on the relationship between the quantizer performance function and the source variance. The third design uses a new algorithm to determine stepwise optimum VQ codebook rates to minimize rate while limiting distortion. Quad-trees are used in all cases to communicate block sizes to the receiver. Simulations show that these variable rate VQs encode over 70 percent of the Lena image at a very low rate while maintaining good fidelity. The proposed schemes also preserve edge fidelity, even at low rates.

Paper Details

Date Published: 5 September 1989
PDF: 12 pages
Proc. SPIE 1099, Advances in Image Compression and Automatic Target Recognition, (5 September 1989); doi: 10.1117/12.960463
Show Author Affiliations
Chung-yen Chiu, University of California (United States)
Richard L. Baker, University of California (United States)

Published in SPIE Proceedings Vol. 1099:
Advances in Image Compression and Automatic Target Recognition
Andrew G. Tescher, Editor(s)

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