Automatic regularization parameter selection by generalized cross-validation for total variational Poisson noise removal

Directional Total Generalized Variation Regularization for Impulse Noise Removal

Large-scale Inversion of Magnetic Data Using Golub-Kahan Bidiagonalization with Truncated Generalized Cross Validation for Regularization Parameter Estimation

In this paper a fast method for large-scale sparse inversion of magnetic data is considered. The L1-norm stabilizer is used to generate models with sharp and distinct interfaces. To deal with the non-linearity introduced by the L1-norm, a model-space iteratively reweighted least squares algorithm is used. The original model matrix is factorized using the Golub-Kahan bidiagonalization that proje...

The generalized cross validation method for the selection of regularization parameter in geophysical diffraction tomography

Inverse problems are usually ill-posed in such a way that it is necessary to use some method to reduce their deficiencies. The method that we choose is the regularization by derivative matrices. There is a crucial problem in regularization, which is the selection of the regularization parameter λ. In this work we use generalized cross validation (GCV) as a tool for the selection of λ. GCV was p...

Multilevel algorithm for a Poisson noise removal model with total-variation regularization

Many commonly used models for the fundamental image processing task of noise removal can deal with Gaussian white noise. However such Gaussian models are not effective to restore images with Poisson noise, which is ubiquitous in certain applications. Recently Le-Chartrand-Asaki derived a new data-fitting term in the variational model for Poisson noise. This paper proposes a multilevel algorithm...

Automatic estimation of regularization parameter by active constraint balancing method for 3D inversion of gravity data

Gravity data inversion is one of the important steps in the interpretation of practical gravity data. The inversion result can be obtained by minimization of the Tikhonov objective function. The determination of an optimal regularization parameter is highly important in the gravity data inversion. In this work, an attempt was made to use the active constrain balancing (ACB) method to select the...