Multispectral inverse problems in satellite image processing

Scott A. Starks; Vladik Kreinovich

doi:10.1117/12.323793

22 September 1998 Multispectral inverse problems in satellite image processing

Scott A. Starks, Vladik Kreinovich

Proceedings Volume 3459, Bayesian Inference for Inverse Problems; (1998) https://doi.org/10.1117/12.323793
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

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.

Citation Download Citation

Scott A. Starks and Vladik Kreinovich "Multispectral inverse problems in satellite image processing", Proc. SPIE 3459, Bayesian Inference for Inverse Problems, (22 September 1998); https://doi.org/10.1117/12.323793

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