Image reconstruction using an iterative SOM based algorithm

The frequent presence of clouds in optical remotely sensed imagery prevents space and time continuity and limits its exploitation. The aim of this study is to propose a new statistical processing approach for the reconstruction of areas covered by clouds in a time sequence of optical satellite images. The approach is an iterative SOM based algorithm and is applied here to reconstruct ocean color images. It used the information contained in ocean color images and a set of satellite-derived dynamic ocean products (sea surface temperature: SST, altimetry: SSH) to reproduce the local spatio-temporal relationships of the cloudy images. The reconstruction method is general and can be extended to similar problems.