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Proceedings Paper

Localized processing for hyperspectral image analysis
Author(s): Qian Du
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Paper Abstract

Target detection is one of the major tasks in hyperspectral image analysis. Constrained Energy Minimization (CEM) is a popular technique for target detection. It designs a finite impulse response filter in such a manner that the filter output energy is minimized subject to a constraint imposed by the desired target of interest. It is particular useful when only the desired target signature is available. When those undesired signatures to be eliminated are also known, Target Constrained Interference Minimization Filter (TCIMF) can be used to minimize the output of undesired signatures to further improve the performance. It has been demonstrated that TCIMF can better differentiate targets with similar spectral signatures. Both CEM and TCIMF involve the calculation of the data sample correlation matrix R and its inverse matrix R-1. The function of R-1 is background suppression. When the target to be detected is very small and embedded at the sub-pixel level, it is difficult to detect it. But if the data sample correlation matrix R can well present the statistics of the background surrounding the pixel containing the object such that R-1 can well suppress the background, the target may still have a chance to be detected. So in this paper we propose a localized processing technique. Instead of using all the pixels in an image scene to calculate the R, only several lines of pixels near the pixel to be processed are used for the R computation. The preliminary result using an HYDICE image scene demonstrates the effectiveness of such a localized processing technique in the detection of targets at sub-pixel level. Interestingly, in some cases it can also improve the performance of CEM in target discrimination.

Paper Details

Date Published: 14 December 2004
PDF: 8 pages
Proc. SPIE 5584, Chemical and Biological Standoff Detection II, (14 December 2004); doi: 10.1117/12.570784
Show Author Affiliations
Qian Du, Mississippi State Univ. (United States)

Published in SPIE Proceedings Vol. 5584:
Chemical and Biological Standoff Detection II
James O. Jensen; Jean-Marc Theriault, Editor(s)

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