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Proceedings Paper

Kalman filter-based approaches to hyperspectral signature similarity and discrimination
Author(s): Su Wang; Chein-I Chang; Janet L. Jensen; J. O. Jensen
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Paper Abstract

Kalman filter has been widely used in statistical signal processing for parameter estimation. Recently, a Kalman filter-based approach to spectral unmixing, referred to as Kalman filter-based linear unmixing (KFLU) was also developed for mixed pixel classification. However, its applicability to estimation and discrimination for hyperspectral signature characterization has not been explored where a hyperspectral signature is defined as a vector on a range of contiguous optical wavelengths of interest. This paper presents a new application of Kalman filtering in hyperspectral signature similarity and discrimination. In particular, it develops a Kalman filter-based signature estimator from which two Kalman filter-based discriminators can be derived for signature similarity and discrimination. The developed Kalman filter-based discriminators utilize a state equation to characterize a hyperspectral signature and a measurement equation to describe another hyperspectral signature, while the developed Kalman filter-based estimator makes use of state and measurement equations to describe the true signature and the observable signature respectively. The least squares error resulting from the Kalman filter-estimated hyperspectral signature is then used as the power for hyperspectral signature similarity and discrimination. Experimental results demonstrate that such Kalman filter-based discriminators are more effective than commonly used spectral similarity measures such as spectral angle mapper (SAM) or Euclidean distance.

Paper Details

Date Published: 1 September 2006
PDF: 12 pages
Proc. SPIE 6302, Imaging Spectrometry XI, 63020J (1 September 2006); doi: 10.1117/12.681663
Show Author Affiliations
Su Wang, Univ. of Maryland, Baltimore County (United States)
Chein-I Chang, Univ. of Maryland, Baltimore County (United States)
Janet L. Jensen, U.S. Army Edgewood Chemical and Biological Ctr. (United States)
J. O. Jensen, U.S. Army Edgewood Chemical and Biological Ctr. (United States)


Published in SPIE Proceedings Vol. 6302:
Imaging Spectrometry XI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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