A New Total Variation Method for Multiplicative Noise Removal

where α1 and α2 are positive regularization parameters. The main advantage of using the new data fitting term ∑n2 i=1 ( [z]i + [g]iei ) is that its second derivative with respect to [z]i is equal to [g]i e−[z]i , therefore it implies that the new data fitting term is strictly convex for all z. Here we add a fitting term ||z −w||2 in the new minimization method. We can interpret the total variation minimization scheme to denoise the multiplicative noise removed image z. The main advantage of the proposed method is that an exact TV norm is used in the noise removal process. Therefore the new method has the ability to preserve edges very well in the denoised image.