NDLI: A Parametric Estimation Approach to Instantaneous Spectral Imaging

Content Provider	IEEE Xplore Digital Library
Author	Oktem, F.S. Kamalabadi, F. Davila, J.M.
Copyright Year	1992
Abstract	Spectral imaging, the simultaneous imaging and spectroscopy of a radiating scene, is a fundamental diagnostic technique in the physical sciences with widespread application. Due to the intrinsic limitation of two-dimensional (2D) detectors in capturing inherently three-dimensional (3D) data, spectral imaging techniques conventionally rely on a spatial or spectral scanning process, which renders them unsuitable for dynamic scenes. In this paper, we present a nonscanning (instantaneous) spectral imaging technique that estimates the physical parameters of interest by combining measurements with a parametric model and solving the resultant inverse problem computationally. The associated inverse problem, which can be viewed as a multiframe semiblind deblurring problem (with shift-variant blur), is formulated as a maximum a posteriori (MAP) estimation problem since in many such experiments prior statistical knowledge of the physical parameters can be well estimated. Subsequently, an efficient dynamic programming algorithm is developed to find the global optimum of the nonconvex MAP problem. Finally, the algorithm and the effectiveness of the spectral imaging technique are illustrated for an application in solar spectral imaging. Numerical simulation results indicate that the physical parameters can be estimated with the same order of accuracy as state-of-the-art slit spectroscopy but with the added benefit of an instantaneous, 2D field-of-view. This technique will be particularly useful for studying the spectra of dynamic scenes encountered in space remote sensing.
Sponsorship	IEEE Signal Processing Society
Starting Page	5707
Ending Page	5721
Page Count	15
File Size	2830020
File Format	PDF
ISSN	10577149
Volume Number	23
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Detectors Imaging Dispersion Diffraction Noise Extraterrestrial measurements Parametric statistics space remote sensing computational spectral imaging imaging spectroscopy inverse methods maximum posterior estimation dynamic programming multiframe image deblurring parameter estimation of superimposed signals separable nonlinear least squares problems Computational spectral imaging
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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