Poisson Noise Removal Scheme Based on Fourth-Order PDE by Alternating Minimization Algorithm

Poisson Noise Removal Scheme Based on Fourth-Order PDE by Alternating Minimization Algorithm

and Applied Analysis 3 2. Existence and Uniqueness In this section, the existence and uniqueness of the minimizer for the model 1.4 are proved. Some basic notations and properties concerning with the BV 2 space can be seen in 8, 13 . Motivated by 5 , we have the following existence and uniqueness result for the optimization problem 1.4 . Theorem 2.1. Assume Ω is an open, bounded Lipschitz domai...

Lysaker, Lundervold, Tai: Noise Removal in Mri Using Fourth-order Pde

Alternating Minimization Algorithm with Automatic Relevance Determination for Transmission Tomography under Poisson Noise

We propose a globally convergent alternating minimization (AM) algorithm for image reconstruction in transmission tomography, which extends automatic relevance determination (ARD) to Poisson noise models with Beer’s law. The algorithm promotes solutions that are sparse in the pixel/voxeldifferences domain by introducing additional latent variables, one for each pixel/voxel, and then learning th...

Multiplicative noise removal using primal–dual and reweighted alternating minimization

Multiplicative noise removal is an important research topic in image processing field. An algorithm using reweighted alternating minimization to remove this kind of noise is proposed in our preliminary work. While achieving good results, a small parameter is needed to avoid the denominator vanishing. We find that the parameter has important influence on numerical results and has to be chosen ca...

Fast linearized alternating direction minimization algorithm with adaptive parameter selection for multiplicative noise removal

Owing to the edge preserving ability and low computational cost of the total variation (TV), variational models with the TV regularization have been widely investigated in the field of multiplicative noise removal. The key points of the successful application of these models lie in: the optimal selection of the regularization parameter which balances the data-fidelity term with the TV regulariz...