Abstract: Interactive analysis of massive data sets acquired by different remote sensors (RS) in microwave (MW), infrared (IR), and visible (V) bands requires special methods and algorithms. Different kind of noises and inaccuracies can deteriorate input data and give rise to considerable errors when an illposed inverse problem is solved. We are further developing a processing system to analyze multitemporal and multispectral images of different objects. The main advantages of this system are: the possibilities to restore 2D multispectral (multitemporal) images, and to find the highest correlation regions on an image produced by different sensors (MW: dm, cm, mm, SAR and non SAR; IR and V and oth) as well as the use of the new robust order-statistic filtering procedures proposed. Different RS problems have been investigated: rural or vegetation covered areas sensed by MW airborne sensors; forest fire areas, industrial plants in the night, electrical power elements (IR and V airborne sensors). Numerical simulation and experimental results have shown the efficiency of the proposed restoration and order-statistic filtering techniques. !9
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