Simulated annealing algorithm for ill-posed or ill-conditioning deconvolution problem

A simulated annealing deconvolution technique dealing with the ill-posed and ill-Conditioning problems is presented. Following a survey about direct and iterative deconvolution techniques, the simulated annealing approach for ill-posed and ill-conditioning decon volution is introduced. With comparison to some deconvolution techniques the new approach is described in details. A specific ill-posed and ill-Conditioning deconvolution example is consid ered and the deconvolution results using the simulated annealing approach and some conventional techniques such as clipped inverse filtering, reblurring, multiple-operator, constrained iteration, etc., are given. It has shown that the simulated annealing approach fights against the ill-posed and ill-conditioning successfully.