Share Email Print

Proceedings Paper

Spectral abundance fraction estimation of materials using Kalman filters
Author(s): Su Wang; Chein Chang; Janet L. Jensen; James O. Jensen
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Kalman filter has been widely used in statistical signal processing for parameter estimation. Although a Kalman filter approach has been recently developed for spectral unmixing, referred to as Kalman filter-based linear unmixing (KFLU), its applicability to spectral characterization within a single pixel vector has not been explored. This paper presents a new application of Kalman filtering in spectral estimation and quantification. It develops a Kalman filter-based spectral signature esimator (KFSSE) which is different from the KFLU in the sense that the former performs a Kalman filter wavelength by wavelength across a spectral signature as opposed to the latter which implements a Kalman filter pixel vector by pixel vector in an image cube. The idea of the KFSSE is to implement the state equation to characterize the true spectral signature, while the measurement equation is being used to describe the spectral signature to be processed. Additionally, since a Kalman filter can accurately estimate spectral abundance fraction of a signature, our proposed KFSSE can further used for spectral quantification for subpixel targets and mixed pixel vectors, called Kalman filter-based spectral quantifier (KFSQ). Such spectral quantification is particularly important for chemical/biological defense which requires quantification of detected agents for damage control assessment. Several different types of hyperspectral data are used for experiments to demonstrate the ability of the KFSSE in estimation of spectral signature and the utility of the KFSQ in spectral quantification.

Paper Details

Date Published: 14 December 2004
PDF: 11 pages
Proc. SPIE 5584, Chemical and Biological Standoff Detection II, (14 December 2004); doi: 10.1117/12.572385
Show Author Affiliations
Su Wang, Univ. of Maryland/Baltimore County (United States)
Chein Chang, Univ. of Maryland/Baltimore County (United States)
Janet L. Jensen, U.S. Army Edgewood Chemical Biological Ctr. (United States)
James O. Jensen, U.S. Army Edgewood Chemical Biological Ctr. (United States)

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

© SPIE. Terms of Use
Back to Top