A generalized approach for atomic force microscopy image restoration with bregman distances as tikhonov regularization terms

摘要

Tikhonv's regularization approach applied to image resportation, stated in terms of ill-posed roblems, has proved to be a pow3erful tool to solve noisy and imcomplete data. This work proposes a variable norm discrepancy function as the regularization term, where the entropy functional was derived. Our method is applied to true Atomic Force Microscopy (AFM) biological images, producing satisfactory results. These images represent a mapping of local interaction forces exerted between a reduced scaled AFM sensing tip and the biologicaol smaple, kept alive in aqueous or air environment.