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Proceedings Paper

Target detection in hyperspectral images using projection pursuit with interference rejection
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Paper Abstract

We present a method for the automatic, unsupervised detection of spectrally distinct targets from the background using hyperspectral imaging. The approach is based on the concepts of projection pursuit (PP) and unsupervised orthogonal subspace projection (UOSP). It has the advantage of not requiring any prior knowledge of the scene or the objects' spectral signatures. All information is obtained from the data. First, PP is used to both reduce the data dimensionality and locate potential targets. Then, UOSP suppresses the signatures from undesired objects or interferers that cause false detections when a spectral filter is applied. The result is a set of gray scale images where objects belonging to the same spectral class are enhanced while the background and other undesired objects are suppressed. This method is demonstrated using data from the Hyperspectral Digital Imagery Collection Experiment (HYDICE).

Paper Details

Date Published: 4 December 1998
PDF: 9 pages
Proc. SPIE 3500, Image and Signal Processing for Remote Sensing IV, (4 December 1998); doi: 10.1117/12.331893
Show Author Affiliations
Agustin I. Ifarraguerri, U.S. Army Edgewood Research, Development, and Engineering Ctr. (United States)
Hsuan Ren, Univ. of Maryland/Baltimore County (United States)
Chein-I Chang, Univ. of Maryland/Baltimore County (United States)


Published in SPIE Proceedings Vol. 3500:
Image and Signal Processing for Remote Sensing IV
Sebastiano Bruno Serpico, Editor(s)

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