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Proceedings Paper

Multispectral inverse problems in satellite image processing
Author(s): Scott A. Starks; Vladik Kreinovich
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Paper Abstract

Satellite imaging is nowadays one of the main sources of geophysical and environmental information. It is, therefore, extremely important to be able to solve the corresponding inverse problem,: reconstruct the actual geophysics- or environmental-related image from the observed noisy data. Traditional image reconstruction techniques have been developed for the case when we have a single observed image. This case corresponds to a single satellite photo. Existing satellites take photos in several wavelengths. To press this multiple-spectral information, we can use known reasonable multi-image modifications of the existing single-image reconstructing techniques. These modifications, basically, handle each image separately, and try to merge the resulting information. Currently, a new generation of image satellites is being launched, that will enable us to collect visual images for about 500 different wavelengths. This two order of magnitude increase in data amount should lead to a similar increase in the processing time, but surprisingly, it does not. An analysis and explanation of this paradoxical simplicity is given in the paper.

Paper Details

Date Published: 22 September 1998
PDF: 9 pages
Proc. SPIE 3459, Bayesian Inference for Inverse Problems, (22 September 1998); doi: 10.1117/12.323793
Show Author Affiliations
Scott A. Starks, NASA Pan-American Ctr. for Earth and Environmental Studies (United States)
Vladik Kreinovich, Univ. of Texas at El Paso (United States)

Published in SPIE Proceedings Vol. 3459:
Bayesian Inference for Inverse Problems
Ali Mohammad-Djafari, Editor(s)

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