IMAGE COMPRESSION VIA VECTOR QUANTIZATION WITH VARIABLE DIMENSION.

Yasuo Matsuyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Novel vector-quantization algorithms are given and applied to image compression. These algorithms extend the conventional algorithms which is a direct generalization of the classical Lloyd-Max type. The quantizer generates subregions of convex polygons with different sizes. Novel size of the convex polygon is chosen so that the total distortion of the training or source image to a given codebook is minimized. Experiments on 8-b/pixel images show that the optimization of the variable-region (or variable-dimension) vector quantization subdivides the original rectilinear pixel array into versatile convex polygons allowing slant edges.

Original languageEnglish
Title of host publicationUnknown Host Publication Title
Place of PublicationNew York, NY, USA
PublisherIEEE
Pages423-427
Number of pages5
Publication statusPublished - 1987
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Matsuyama, Y. (1987). IMAGE COMPRESSION VIA VECTOR QUANTIZATION WITH VARIABLE DIMENSION. In Unknown Host Publication Title (pp. 423-427). IEEE.