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Abstract

Sensitivity to weather conditions, and specially to clouds, is a severe limiting factor to the use of optical remote sensing for Earth monitoring applications. Typically, the optical satellite images are often corrupted because of poor weather conditions. As a rule, the measure of degradation of optical images is such that one can not rely even on the brightness inside of the damaged regions. As a result, some subdomains of such images become absolutely invisible. So, there is a risk of information loss in optical remote sensing data. In view of this, we propose a new variational approach for exact restoration of multispectral satellite optical images. We discuss the consistency of the proposed variational model, give the scheme for its regularization, derive the corresponding optimality system, and discuss the algorithm for the practical implementation of the reconstruction procedure. Experimental results are very promising and they show a significant gain over baseline methods using the reconstruction through linear interpolation between data available at temporally-close time instants. © 2021 Copyright for this paper by its authors.