Paper
22 October 1993 Affine-transform-based image vector quantizer
Madaparthi B. Brahmanandam, Sethuraman Panchanathan, Morris Goldberg
Author Affiliations +
Proceedings Volume 2094, Visual Communications and Image Processing '93; (1993) https://doi.org/10.1117/12.157923
Event: Visual Communications and Image Processing '93, 1993, Cambridge, MA, United States
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.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Madaparthi B. Brahmanandam, Sethuraman Panchanathan, and Morris Goldberg "Affine-transform-based image vector quantizer", Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); https://doi.org/10.1117/12.157923
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KEYWORDS
Quantization

Distortion

Image transmission

Image compression

Computer programming

Analytical research

Electrical engineering

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