Target Detection in Hyperspectral Images Based on Independent Component Analysis

  title={Target Detection in Hyperspectral Images Based on Independent Component Analysis},
  author={Stefan A. Robilaa and Pramod K. Varshneyb},
  • Stefan A. Robilaa, Pramod K. Varshneyb
  • Published 2003
The paper presents an algorithm based on Independent Component Analysis (ICA) for the detection of small targets present in hyperspectral images. ICA is a multivariate data analysis method that attempts to produce statistically independent components. This method is based on fourth order statistics. Small, man-made targets in a natural background can be seen as anomalies in the image scene and correspond to independent components in the ICA model. The algorithm described here starts by… CONTINUE READING
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Independent Component Analysis

  • T. W. Lee
  • Theory and Applications, Kluwer Academic…
  • 1998
Highly Influential
6 Excerpts

Blind separation of spectral signatures in hyperspectral imagery

  • T. M. Tu, P. S. Huang, P. Y. Chen
  • IEE Proceedings on Vision, Image and Signal…
  • 2001
2 Excerpts

Unsupervised hyperspectral image analysis using independent component analysis

  • S-S. Chiang, C-I. Chang, I. W. Ginsberg
  • Proceedings of IEEE Geoscience and Remote Sensing…
  • 2000
2 Excerpts

Independent component analysis for remote sensing

  • C. H. Chen, X. Zhang
  • Proceedings of SPIE Image and Signal Processing…
  • 1999
1 Excerpt

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