Paper
1 May 1986 Image Coding by Vector Quantization of M-Hadamard Transform Coefficients
Bernard Hammer, Michael Schielein
Author Affiliations +
Proceedings Volume 0594, Image Coding; (1986) https://doi.org/10.1117/12.952198
Event: 1985 International Technical Symposium/Europe, 1985, Cannes, France
Abstract
Vector quantization (VQ) has been recognized to be a promising technique for low data rate image coding as a result of the development of effective codebook design algorithms and advances in digital processing. VQ in the transform domain of the so-called M-Hadamard Transform is proposed to avoid typical quantization noise of VQ, namely block contouring and the 'staircase' reconstruction of edges in the decoded image which is highly noticeable by the human observer. This contribution reports the application of this principle in an intra/interframe coder concept for encoding the luminance component of TV-sequences with fixed length codewords of 1 bit/sample. In particular a vector predictive quantizer is used for encoding the inter-frame block differences of the image sequence. This is supported by a memoryless VQ to improve prediction in blocks with strong movement. The codebook of the VQ is based on the well-known LGB-algorithm.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bernard Hammer and Michael Schielein "Image Coding by Vector Quantization of M-Hadamard Transform Coefficients", Proc. SPIE 0594, Image Coding, (1 May 1986); https://doi.org/10.1117/12.952198
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Cited by 2 scholarly publications.
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KEYWORDS
Image compression

Quantization

Signal to noise ratio

Computer programming

Image processing

Distortion

Visibility

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