Remote sensing by microwave, infrared and visible sensors for information extraction by novel deconvolution and filtering algorithms

We present a novel and mathematically sustained procedures for solving deconvolution-filtering problem. The technique for obtaining a stable solution to the deconvolution (restoration) problem is based on the regularized functional Newman serias of the operator equations and gives more precise results than traditional ones. It was proposed several novel rank filtering procedures for decreasing of noise influences. These procedures have given more accuracy and robust results in comparison with known ones. The efficiency of the techniques proposed hove been proved by numerical simulation analysis and by experimental investigations of different kinds of RS objects: • rural or vegetation covered areas sensed by three microwave frequencies airborne equipment. • forest fire areas, industrial installations at night, electrical structures, etc. sensed by infrared and visible sensors; • tropospheric refractive index height profiles restoration by satellite navigation system "CIKADA" data.