Enhanced Detection and Visualization of Anomalies in Spectral Imagery

@inproceedings{Basener2009EnhancedDA,
  title={Enhanced Detection and Visualization of Anomalies in Spectral Imagery},
  author={William F Basener and David W. Messinger},
  year={2009}
}
Anomaly detection algorithms applied to hyperspectral imagery are able to reliably identify man-made objects from a natural environment based on statistical/geometric likelyhood. The process is more robust than target identification, which requires precise prior knowledge of the object of interest, but has an inherently higher false alarm rate. Standard anomaly detection algorithms measure deviation of pixel spectra from a parametric model (either statistical or linear mixing) estimating the… CONTINUE READING
Highly Cited
This paper has 28 citations. REVIEW CITATIONS
23 Citations
9 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 23 extracted citations

References

Publications referenced by this paper.
Showing 1-9 of 9 references

Anomaly detection using topology

  • W. Basener, I.E., D. Messinger
  • Algorithms and Technologies for Multispectral…
  • 2007

A nested window-based approach to target detection for hyperspectral imagery

  • Chang, C.-I., W. Lui
  • IEEE International Geoscience and Remote Sensing…
  • 2004

Adaptive anomaly detection using subspace separation for hyperspectral imagery

  • S.Z.D.H. Kwon, N. Nasrabadi
  • Opt. Eng. (October 2003).
  • 2003

Spectral subspace matched filtering

  • A. Schaum
  • Algorithms for multispectral, hyperspectral, and…
  • 2001

Detection and classification of subpixel spectral signatures in hyperspectral image sequences

  • J. C. Harsanyi, F.W.C.C.-I.
  • Proc. Amer. Soc. Photogram. Remote Sens. , 236…
  • 1994

Detection and classification of subpixel spectral signatures in hyperspectral imaging sequences

  • J. C. Harsanyi
  • Ph.D. Dissertation,, Dept. Elect. Eng., Univ…
  • 1993

Similar Papers

Loading similar papers…