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 environment-related image from the observed noisy data. Traditional image reconstruction techniques have been developed for the case when we h a ve a single observed image. This case corresponds to a single satellite photo. Existing satellites (e.g., Landsat) take

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... s in several (up to 7) wavelengths. To process this multiple-spectral information, we can use known reasonable multi-image modi cations of the existing single-image reconstructing techniques. These modi cations, basically, handle each image separately, and try to merge the resulting information. Currently, a new generation of imaging satellites (Lewis) is being launched, that will enable us to collect visual images for about 500 di erent w avelengths. 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 i s g i v en in the paper.