Poisson Noise Removal with Total Variation Regularization and Local Fidelity
Fang Li, Ruihua Liu · 2012
In this paper, we propose two methods to choose the fidelity parameter in total variation based de- noising model for Poisson noise. Firstly, we derive a scheme to choose the scalar parameter automatically. Secondly, we propose to use a local fidelity term with spatial-varying parameters which automatically controls the extent of de- noising according to image contents. Experiments with simulated data demonstrate that the proposed algorithms are effective.