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The object reconstruction from synthesized and noisy photothermal signals was carried out by deconvoluting contrast scans by means of photothermal point spread function. The unknown defect depth parameter was estimated by minimizing the "imaginary content" of the deconvoluted real valued defect distribution. The algorithm shows remarkable accuracy even in the presence of 10%-noise in finding the true defect depth. Essential for its convergence is an effective noise suppression which we achieved by a modified Wiener filter

A proposal for the reconstruction of buried defects from photothermal images