IMAGE COMPRESSION VIA VECTOR QUANTIZATION WITH VARIABLE DIMENSION.

Yasuo Matsuyama

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルUnknown Host Publication Title
Place of PublicationNew York, NY, USA
出版社IEEE
ページ423-427
ページ数5
出版ステータスPublished - 1987
外部発表はい

ASJC Scopus subject areas

  • Engineering(all)

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