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Proceedings Paper

Affine-transform-based image vector quantizer
Author(s): Madaparthi B. Brahmanandam; Sethuraman Panchanathan; Morris Goldberg
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Paper Abstract

In this paper, we propose an affine transform based vector quantization (ATVQ) technique for image coding applications. Vector quantization (VQ) is intrinsically superior to predictive coding, transform coding, and other suboptimal and ad hoc procedures. The limitation of VQ is the very large codebook that must be generated and stored. The proposed affine transform based vector quantization technique addresses this problem. The image to be coded is partitioned into disjoint square blocks. Each block is regarded as a vector and is encoded by searching through a set of affine transforms and a codebook of templates. The transform- template pair that can reconstruct an approximate input vector with minimum distortion is selected. The parameters and the index of the affine transform and the index of the template constitute the codeword of the input vector. In decoding, the image vector is reconstructed by applying the inverse of the affine transform on the template. ATVQ can reconstruct more input vectors without any distortion than conventional VQ can reconstruct, using the same codebook. Simulation results show that the technique performs well using a universal codebook. This technique is also suitable for progressive image transmission as its performance is good at very low bit rates.

Paper Details

Date Published: 22 October 1993
PDF: 10 pages
Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); doi: 10.1117/12.157923
Show Author Affiliations
Madaparthi B. Brahmanandam, Univ. of Ottawa (Canada)
Sethuraman Panchanathan, Univ. of Ottawa (Canada)
Morris Goldberg, Univ. of Ottawa (France)


Published in SPIE Proceedings Vol. 2094:
Visual Communications and Image Processing '93
Barry G. Haskell; Hsueh-Ming Hang, Editor(s)

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