Two iterative methods of decomposition of a fuzzy relation for image compression/decompression processing

H. Nobuhara; K. Hirota; W. Pedrycz; S. Sessa

doi:10.1007/s00500-003-0319-6

Two iterative methods of decomposition of a fuzzy relation for image compression/decompression processing

H. Nobuhara^*, K. Hirota, W. Pedrycz, S. Sessa

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

A decomposition problem of max-min type for a fuzzy relation is proposed. A fast method is derived by transforming slightly the derivatives in the traditional gradient algorithm and by updating simultaneously the prototype relation. The complexities of the proposed algorithm, with respect to the traditional gradient one, are decreased to approximately 1/c, where "c" denotes the Schein rank of the fuzzy relation involved. A dual decomposition problem of max-min type is also formulated and a similar fast method is presented. Both methods are applied to image compression/decompression processing.

Original language	English
Pages (from-to)	698-704
Number of pages	7
Journal	Soft Computing
Volume	8
Issue number	10
DOIs	https://doi.org/10.1007/s00500-003-0319-6
Publication status	Published - 2004
Externally published	Yes

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AB - A decomposition problem of max-min type for a fuzzy relation is proposed. A fast method is derived by transforming slightly the derivatives in the traditional gradient algorithm and by updating simultaneously the prototype relation. The complexities of the proposed algorithm, with respect to the traditional gradient one, are decreased to approximately 1/c, where "c" denotes the Schein rank of the fuzzy relation involved. A dual decomposition problem of max-min type is also formulated and a similar fast method is presented. Both methods are applied to image compression/decompression processing.

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Two iterative methods of decomposition of a fuzzy relation for image compression/decompression processing

Abstract

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