Iterative total variation schemes for nonlinear inverse problems
暂无分享,去创建一个
[1] Hui Huang,et al. On Effective Methods for Implicit Piecewise Smooth Surface Recovery , 2006, SIAM J. Sci. Comput..
[2] Curtis R. Vogel,et al. Iterative Methods for Total Variation Denoising , 1996, SIAM J. Sci. Comput..
[3] I. Ekeland,et al. Convex analysis and variational problems , 1976 .
[4] L. Bregman. The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming , 1967 .
[5] Karl Kunisch,et al. Some applications of BV functions in optimal controls and calculus of variations , 1998 .
[6] M. Hanke. A regularizing Levenberg - Marquardt scheme, with applications to inverse groundwater filtration problems , 1997 .
[7] Wotao Yin,et al. Bregman Iterative Algorithms for (cid:2) 1 -Minimization with Applications to Compressed Sensing ∗ , 2008 .
[8] C. Vogel. Computational Methods for Inverse Problems , 1987 .
[9] B. Kaltenbacher,et al. Iterative methods for nonlinear ill-posed problems in Banach spaces: convergence and applications to parameter identification problems , 2009 .
[10] I. Daubechies,et al. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint , 2003, math/0307152.
[11] Lin He,et al. Blind deconvolution using TV regularization and Bregman iteration , 2005, Int. J. Imaging Syst. Technol..
[12] S. Osher,et al. Nonlinear inverse scale space methods , 2006 .
[13] Wotao Yin,et al. An Iterative Regularization Method for Total Variation-Based Image Restoration , 2005, Multiscale Model. Simul..
[14] M. Hanke,et al. A convergence analysis of the Landweber iteration for nonlinear ill-posed problems , 1995 .
[15] L. Rudin,et al. Nonlinear total variation based noise removal algorithms , 1992 .
[16] Tal Schuster,et al. Nonlinear iterative methods for linear ill-posed problems in Banach spaces , 2006 .
[17] Stanley Osher,et al. Iterative Regularization and Nonlinear Inverse Scale Space Applied to Wavelet-Based Denoising , 2007, IEEE Transactions on Image Processing.
[18] Jian-Feng Cai,et al. Convergence of the linearized Bregman iteration for ℓ1-norm minimization , 2009, Math. Comput..
[19] Antonin Chambolle,et al. Nonlinear wavelet image processing: variational problems, compression, and noise removal through wavelet shrinkage , 1998, IEEE Trans. Image Process..
[20] Gene H. Golub,et al. A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration , 1999, SIAM J. Sci. Comput..
[21] ANTONIN CHAMBOLLE,et al. An Algorithm for Total Variation Minimization and Applications , 2004, Journal of Mathematical Imaging and Vision.
[22] C. Vogel,et al. Analysis of bounded variation penalty methods for ill-posed problems , 1994 .
[23] Jian-Feng Cai,et al. Linearized Bregman iterations for compressed sensing , 2009, Math. Comput..
[24] Karl Kunisch,et al. Total Bounded Variation Regularization as a Bilaterally Constrained Optimization Problem , 2004, SIAM J. Appl. Math..
[25] Marc Teboulle,et al. Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions , 1993, SIAM J. Optim..
[26] H. Engl,et al. Regularization of Inverse Problems , 1996 .
[27] R. Luce,et al. Parameter identification for an elliptic partial differential equation with distributed noisy data , 1999 .
[28] O. Scherzer,et al. Error estimates for non-quadratic regularization and the relation to enhancement , 2006 .
[29] Jian-Feng Cai,et al. Linearized Bregman Iterations for Frame-Based Image Deblurring , 2009, SIAM J. Imaging Sci..
[30] Lin He,et al. Iterative Total Variation Regularization with Non-Quadratic Fidelity , 2006, Journal of Mathematical Imaging and Vision.
[31] Emmanuel J. Candès,et al. Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? , 2004, IEEE Transactions on Information Theory.