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Proceedings Paper

Image Coding by Vector Quantization of M-Hadamard Transform Coefficients
Author(s): Bernard Hammer; Michael Schielein
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Paper 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.

Paper Details

Date Published: 1 May 1986
PDF: 7 pages
Proc. SPIE 0594, Image Coding, (1 May 1986); doi: 10.1117/12.952198
Show Author Affiliations
Bernard Hammer, Siemens AG (Federal Republic of Germany)
Michael Schielein, Siemens AG (Federal Republic of Germany)


Published in SPIE Proceedings Vol. 0594:
Image Coding
Thomas S. Huang; Murat Kunt, Editor(s)

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