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Proceedings Paper

Image coding through predictive vector quantization
Author(s): Ajai Narayan; Tenkasi V. Ramabadran
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Paper Abstract

This paper describes a predictive vector quantizer (PVQ) for coding grayscale images. The method described can be regarded as an extension of an existing speech coding algorithm in 1- dimension to 2-dimensional images. The method applies vector quantization (VQ) to innovations generated by the well known scalar differential pulse code modulation (DPCM) method. It tries to exploit the advantages of both the simplicity of DPCM and the high compressibility of VQ. Two types of code books, viz., random and deterministic, are used in the implementation. Performance results of the method with both types of codebooks are presented for industrial radiographic images. The results are also compared with reconstructions obtained using the discrete cosine transform (DCT) method.

Paper Details

Date Published: 12 January 1993
PDF: 10 pages
Proc. SPIE 1771, Applications of Digital Image Processing XV, (12 January 1993); doi: 10.1117/12.139093
Show Author Affiliations
Ajai Narayan, Iowa State Univ. (United States)
Tenkasi V. Ramabadran, Iowa State Univ. (United States)

Published in SPIE Proceedings Vol. 1771:
Applications of Digital Image Processing XV
Andrew G. Tescher, Editor(s)

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