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Hierarchical clustering algorithms for segmentation of multispectral images

  • I. A. Pestunov
  • S. A. Rylov
  • V. B. Berikov
Analysis and Synthesis of Signals and Images

Abstract

Computationally efficient HCA and HECA hierarchical clustering algorithms for segmentation of multispectral images have been developed using the grid and ensemble approaches. A special metric is proposed to identify embedded clusters even in the presence of overlapping. The efficiency of the algorithms has been confirmed by the results of experimental studies using model and real data.

Keywords

ensemble hierarchical clustering algorithm grid approach segmentation of multispectral satellite images 

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Copyright information

© Allerton Press, Inc. 2015

Authors and Affiliations

  1. 1.Institute of Computational TechnologiesSiberian Branch of Russian Academy of SciencesNovosibirskRussia
  2. 2.Sobolev Institute of MathematicsSiberian Branch of Russian Academy of SciencesNovosibirskRussia

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