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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 49, Iss. 9 — Mar. 20, 2010
  • pp: 1614–1622

Spectral anomaly detection in deep shadows

Andrey V. Kanaev and Jeremy Murray-Krezan  »View Author Affiliations

Applied Optics, Vol. 49, Issue 9, pp. 1614-1622 (2010)

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Although several hyperspectral anomaly detection algorithms have proven useful when illumination conditions provide for enough light, many of these same detection algorithms fail to perform well when shadows are also present. To date, no general approach to the problem has been demonstrated. In this paper, a novel hyperspectral anomaly detection algorithm that adapts the dimensionality of the spectral detection subspace to multiple illumination levels is described. The novel detection algorithm is applied to reflectance domain hyperspectral data that represents a variety of illumination conditions: well illuminated and poorly illuminated (i.e., shadowed). Detection results obtained for objects located in deep shadows and light–shadow transition areas suggest superiority of the novel algorithm over standard subspace RX detection.

© 2010 Optical Society of America

OCIS Codes
(100.3010) Image processing : Image reconstruction techniques
(100.4145) Image processing : Motion, hyperspectral image processing
(280.4991) Remote sensing and sensors : Passive remote sensing

ToC Category:
Image Processing

Original Manuscript: October 1, 2009
Revised Manuscript: January 28, 2010
Manuscript Accepted: February 3, 2010
Published: March 11, 2010

Andrey V. Kanaev and Jeremy Murray-Krezan, "Spectral anomaly detection in deep shadows," Appl. Opt. 49, 1614-1622 (2010)

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