An Iterative Framework for the Improvement of Soft Clusters for Classificaction

نویسندگان

  • Rhonda D. Phillips
  • Layne T. Watson
  • Randolph H. Wynne
  • Naren Ramakrishnan
چکیده

This work introduces an iterative soft cluster refinement method that extensively uses soft cluster evaluation to determine which clusters would discriminate between classes in a classification scheme. This iterative refinement is part of the continuous iterative guided spectral class rejection (CIGSCR) classification method for remotely sensed images. Results indicate that CIGSCR produces good classifications of remotely sensed images, and classification accuracies are higher using the iterative refinement in CIGSCR than classifications derived from soft clustering without iterative refinement.

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تاریخ انتشار 2009