Color Image Compression Algorithm Using Self-Organizing Feature Map

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概要

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• A new color image compression algorithm using Kohonen’s self-organizing feature map is proposed. Our algorithm is an extension of color image compression algorithm proposed by Pei and Lo [IEEE Trans. Circuits Syst. Video Technol., 8: 191–205 (1998)]. N neurons are introduced in order to reduce a given full color image with 224 colors to an indexed color image with N colors. There are control parameters for the competitive learning among neurons in the self-organizing feature map algorithm. In our proposed algorithm, some of the control parameters, which are included in a neighboring function defined for neurons, are updated by taking relationship among neighboring neurons into account, though all control parameters are updated so as to decrease monotonically and exponentially with respect to each iteration step in Pei and Lo’s algorithm. The color palette obtained by the proposed algorithm is more robust as for control parameters than that by Pei and Lo’s algorithm.

• 東北大学の論文

著者

• Tanaka K

  Department Of Computer And Mathematical Science Graduate School Of Information Sciences Tohoku Unive

• Tanaka Kazuyuki

  Department Of Applied Information Sciences Graduate School Of Information Sciences Tohoku University

• Horiguchi Tsuyoshi

  Department Of Applied Science Faculty Of Engineering Tohoku University

• HOSHI Norihiro

  Department of Computer and Mathematical Science, Graduate School of Information Sciences, Tohoku Uni

• Horiguchi Tsuyoshi

  Department Of Computer And Mathematical Science Graduate School Of Information Sciences Tohoku Unive

• Hoshi Norihiro

  Department Of Computer And Mathematical Science Graduate School Of Information Sciences Tohoku Unive

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