A New Self-Organization Classification Algorithm for Remote-Sensing Images

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概要

• 論文の詳細を見る

• This paper presents a new self-organization classification algorithm for remote-sensing images. Kohonen and other scholars have proposed self-organization algorithms. Kohonen's model easily converges to the local minimum by tuning the elaborate parameters. In addition to others, S.C. Amatur and Y. Takefuji have also proposed self-organization algorithm model. In their algorithm, the maximum neuron model (winner-take-all neuron model) is used where the parameter-tuning is not needed. The algorithm is able to shorten the computation time without a burden on the parameter-tuning. However, their model has a tendency to converge to the local minimum easily. To remove these obstacles produced by the two algorithms, we have proposed a new self-organization algorithm where these two algorithms are fused such that the advantages of the two algorithms are combined. The number of required neurons is the number of pixels multiplied by the number of clusters. The algorithm is composed of two stages: in the first stage we use the maximum self-organization algorithm until the state of the system converges to the local-minimum, then, the Kohonen self-organization algorithm is used in the last stage in order to improve the solution quality by escaping from the local minimum of the first stage. We have slimulated a LANDSAT-TM image data with 500 pixel×100 pixel image and 8-bit gray scaled. The results justifies all our claims to the proposed algorithm.

• 社団法人電子情報通信学会の論文
• 1998-01-25

著者

• Takefuji Yoshiyasu

  Graduate School Of Media And Governance Keio University

• OKA Souichi

  Graduate School of Media and Governance, Keio University

• OGAWA Tomoaki

  Graduate School of Media and Governance, Keio University

• ODA Takayoshi

  Graduate School of Media and Governance, Keio University

• Oka Souichi

  Graduate School Of Media And Governance Keio University

• Oda Takayoshi

  Graduate School Of Media And Governance Keio University

• Ogawa Tomoaki

  Graduate School Of Media And Governance Keio University

関連論文

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• Weighting strategy in the state space problem for DS-CDMA code acquisition (日韓合同ワークショップ 1st Korea-Japan Joint Workshop on Ubiquitous Computing and Networking Systems (ubiCNS 2005))
• A New Self-Organization Classification Algorithm for Remote-Sensing Images

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