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Proceedings Paper

Algorithms for image restoration from acoustic-optical tunable-filter multispectral sensors
Author(s): Keith E. Noren; Jody S. Loyd; Douglas Elgin; Bernard Kerstiens
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Paper Abstract

Multispectral sensing with acoustic-optical tunable filters (AOTFs) offers several advantages for the automated recognition of targets and classification of terrain features. High spectral resolution, real-time selection of the wavelength, and dual polarization are among the chief advantages. AOTFs employed in an imaging sensor usually involve a shifting of the spatial image on the focal plane as the wavelength is sampled. This results in a misregistered data hypercube where selected spectral images are not aligned spatially. This can severely limit the sensor's application if not accounted for and rectified. An edged-based routine operating on data taken with the Real-Time Multispectral Sensor (RTMS), an imaging AOTF sensor produced by the Jet Propulsion Laboratory, will be described and demonstrated in this paper. The method is completely general and is capable of removing misregistration for any reason (e.g. platform jitter) not only for AOTF-induced misregistration. This paper will also provide examples of image classification within several scenes collected by RTMS during tower data collection. The basis for the classification is spectral and/or polarization characteristics of the targets and scenes.

Paper Details

Date Published: 2 July 1998
PDF: 12 pages
Proc. SPIE 3372, Algorithms for Multispectral and Hyperspectral Imagery IV, (2 July 1998); doi: 10.1117/12.312595
Show Author Affiliations
Keith E. Noren, Teledyne Brown Engineering (United States)
Jody S. Loyd, Teledyne Brown Engineering (United States)
Douglas Elgin, Teledyne Brown Engineering (United States)
Bernard Kerstiens, U.S. Army Space and Missile Defense Command (United States)


Published in SPIE Proceedings Vol. 3372:
Algorithms for Multispectral and Hyperspectral Imagery IV
Sylvia S. Shen; Michael R. Descour, Editor(s)

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