Segmentations of hyperspectral imagery: Techniques and applications

Jerry Silverman, Stanley R. Rotman

Research output: Contribution to journalConference articlepeer-review

8 Scopus citations


Several approaches for segmenting hyperspectral data and automatically detecting unusual objects in natural scenes are discussed. We demonstrate segmentations of hyperspectral imagery based on of the most significant principal components of the hyperspectral data cube. Several applications of the segmented data are treated. Digital morphological operations can be used to isolate segments that match target criteria. Alternatively, background segments can be used to define background endmembers; pixels that are quantitatively spectrally different from the background can then be designated. Analog morphological operations can then be used for clutter rejection and for the detection of objects of particular size and shape.

Original languageEnglish
Pages (from-to)334-349
Number of pages16
JournalProceedings of SPIE - The International Society for Optical Engineering
Issue number1
StatePublished - 1 Dec 2002
EventInfrared Technology and Applications XXVIII - Seattle, WA, United States
Duration: 7 Jul 200211 Jul 2002


  • Clustering
  • Hyperspectral data
  • Morphological operations
  • Segmentation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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