Paper
2 July 1998 Algorithms for image restoration from acoustic-optical tunable-filter multispectral sensors
Keith E. Noren, Jody S. Loyd, Douglas Elgin, Bernard Kerstiens
Author Affiliations +
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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Keith E. Noren, Jody S. Loyd, Douglas Elgin, and Bernard Kerstiens "Algorithms for image restoration from acoustic-optical tunable-filter multispectral sensors", Proc. SPIE 3372, Algorithms for Multispectral and Hyperspectral Imagery IV, (2 July 1998); https://doi.org/10.1117/12.312595
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KEYWORDS
Sensors

Polarization

Image registration

Image processing

Crystals

Image sensors

Image segmentation

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