Unsupervised, robust estimation-based clustering of remotely sensed images

  • Nathan S. Netanyahu
  • , James C. Tilton
  • , J. Anthony Gualtieri

Research output: Contribution to journalArticlepeer-review

Abstract

Automated image clustering/classification is a task of considerable importance. To apply this task to remotely sensed imagery, we have pursued an unsupervised clustering scheme based on principles of robust (statistical) estimation. A description of the module employed and results obtained are provided in this paper.
Original languageEnglish
JournalInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2
StatePublished - 1 Jan 1995

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