暂无分享,去创建一个
[1] Simon Setzer,et al. Split Bregman Algorithm, Douglas-Rachford Splitting and Frame Shrinkage , 2009, SSVM.
[2] James V. Lambers,et al. Two New Nonlinear Nonlocal Diffusions for Noise Reduction , 2008, Journal of Mathematical Imaging and Vision.
[3] E. Giusti. Minimal surfaces and functions of bounded variation , 1977 .
[4] Delfim F. M. Torres,et al. Calculus of variations with fractional derivatives and fractional integrals , 2009, Appl. Math. Lett..
[5] Stephan Didas,et al. Relations Between Higher Order TV Regularization and Support Vector Regression , 2005, Scale-Space.
[6] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] J. Aujol,et al. Some algorithms for total variation based image restoration , 2008 .
[8] Pascal Getreuer,et al. Total Variation Inpainting using Split Bregman , 2012, Image Process. Line.
[9] K. B. Oldham,et al. The Fractional Calculus: Theory and Applications of Differentiation and Integration to Arbitrary Order , 1974 .
[10] Tony F. Chan,et al. Euler's Elastica and Curvature-Based Inpainting , 2003, SIAM J. Appl. Math..
[11] Dingyu Xue,et al. Fractional-Order Total Variation Image Restoration Based on Primal-Dual Algorithm , 2013 .
[12] Liang Xiao,et al. Adaptive Fractional-order Multi-scale Method for Image Denoising , 2011, Journal of Mathematical Imaging and Vision.
[13] Jan Modersitzki,et al. Curvature Based Image Registration , 2004, Journal of Mathematical Imaging and Vision.
[14] Pantaleón D. Romero,et al. Blind Deconvolution Models Regularized by Fractional Powers of the Laplacian , 2008, Journal of Mathematical Imaging and Vision.
[15] Y. Nesterov. A method for unconstrained convex minimization problem with the rate of convergence o(1/k^2) , 1983 .
[16] E. Zeidler. Nonlinear Functional Analysis and its Applications: III: Variational Methods and Optimization , 1984 .
[17] Yurii Nesterov,et al. Gradient methods for minimizing composite functions , 2012, Mathematical Programming.
[18] Ke Chen,et al. A Fourth-Order Variational Image Registration Model and Its Fast Multigrid Algorithm , 2011, Multiscale Model. Simul..
[19] Irene Fonseca,et al. A Higher Order Model for Image Restoration: The One-Dimensional Case , 2007, SIAM J. Math. Anal..
[20] Tony F. Chan,et al. High-Order Total Variation-Based Image Restoration , 2000, SIAM J. Sci. Comput..
[21] Karl Kunisch,et al. Total Generalized Variation , 2010, SIAM J. Imaging Sci..
[22] L. Ambrosio,et al. A direct variational approach to a problem arising in image reconstruction , 2003 .
[23] A. N. Tikhonov,et al. Solutions of ill-posed problems , 1977 .
[24] Kim-Chuan Toh,et al. An Accelerated Proximal Gradient Algorithm for Frame-Based Image Restoration via the Balanced Approach , 2011, SIAM J. Imaging Sci..
[25] Teodor M. Atanackovic,et al. Fully fractional anisotropic diffusion for image denoising , 2011, Math. Comput. Model..
[26] P. Guidotti. A new nonlocal nonlinear diffusion of image processing , 2009 .
[27] Lars Hömke,et al. Total Variation Based Image Registration , 2007 .
[28] R. Chan,et al. An Adaptive Strategy for the Restoration of Textured Images using Fractional Order Regularization , 2013 .
[29] Patrick L. Combettes,et al. Signal Recovery by Proximal Forward-Backward Splitting , 2005, Multiscale Model. Simul..
[30] YangQuan Chen,et al. Fractional-order TV-L2 model for image denoising , 2013 .
[31] Marc Teboulle,et al. Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems , 2009, IEEE Transactions on Image Processing.
[32] Sébastien Ourselin,et al. Using fractional gradient information in non-rigid image registration: application to breast MRI , 2012, Medical Imaging.
[33] Wotao Yin,et al. An Iterative Regularization Method for Total Variation-Based Image Restoration , 2005, Multiscale Model. Simul..
[34] Daniel Cremers,et al. TVSeg - Interactive Total Variation Based Image Segmentation , 2008, BMVC.
[35] Otmar Scherzer,et al. Variational Methods in Imaging , 2008, Applied mathematical sciences.
[36] Jian Bai,et al. Fractional-Order Anisotropic Diffusion for Image Denoising , 2007, IEEE Transactions on Image Processing.
[37] Tom Goldstein,et al. The Split Bregman Method for L1-Regularized Problems , 2009, SIAM J. Imaging Sci..
[38] K. Miller,et al. An Introduction to the Fractional Calculus and Fractional Differential Equations , 1993 .
[39] Stefan Henn,et al. Multigrid based total variation image registration , 2008 .
[40] Harald Köstler,et al. Multigrid solution of the optical flow system using a combined diffusion‐ and curvature‐based regularizer , 2008, Numer. Linear Algebra Appl..
[41] Wei Guo,et al. Inpainting based on total variation , 2007, 2007 International Conference on Wavelet Analysis and Pattern Recognition.
[42] I. Podlubny. Fractional differential equations : an introduction to fractional derivatives, fractional differential equations, to methods of their solution and some of their applications , 1999 .
[43] Jean-François Aujol,et al. Projected Gradient Based Color Image Decomposition , 2009, SSVM.
[44] Li Gen-guo,et al. A numerical method for fractional integral with applications , 2003 .
[45] Ke Chen,et al. A new iterative algorithm for mean curvature-based variational image denoising , 2014 .
[46] Pierre Kornprobst,et al. Mathematical problems in image processing - partial differential equations and the calculus of variations , 2010, Applied mathematical sciences.
[47] Xue-Cheng Tai,et al. Noise removal using smoothed normals and surface fitting , 2004, IEEE Transactions on Image Processing.
[48] Mongi A. Abidi,et al. Image restoration using L1 norm penalty function , 2007 .
[49] Yangquan Chen,et al. Matrix approach to discrete fractional calculus II: Partial fractional differential equations , 2008, J. Comput. Phys..
[50] R. Hilfer. Applications Of Fractional Calculus In Physics , 2000 .
[51] Ke Chen,et al. Multigrid Algorithm for High Order Denoising , 2010, SIAM J. Imaging Sci..
[52] Stanley Osher,et al. Image Decomposition and Restoration Using Total Variation Minimization and the H1 , 2003, Multiscale Model. Simul..
[53] A. Atangana,et al. A Note on Fractional Order Derivatives and Table of Fractional Derivatives of Some Special Functions , 2013 .
[54] S. Osher,et al. IMAGE DECOMPOSITION AND RESTORATION USING TOTAL VARIATION MINIMIZATION AND THE H−1 NORM∗ , 2002 .
[55] Arvid Lundervold,et al. Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time , 2003, IEEE Trans. Image Process..
[56] Jean-François Aujol,et al. Some First-Order Algorithms for Total Variation Based Image Restoration , 2009, Journal of Mathematical Imaging and Vision.
[57] E. Zeidler. Nonlinear functional analysis and its applications , 1988 .
[58] Juan Morales-Sánchez,et al. Fractional Regularization Term for Variational Image Registration , 2009 .
[59] Simon Setzer,et al. Operator Splittings, Bregman Methods and Frame Shrinkage in Image Processing , 2011, International Journal of Computer Vision.
[60] O. Marichev,et al. Fractional Integrals and Derivatives: Theory and Applications , 1993 .
[61] G. Jumarie,et al. Modified Riemann-Liouville derivative and fractional Taylor series of nondifferentiable functions further results , 2006, Comput. Math. Appl..
[62] L. Rudin,et al. Nonlinear total variation based noise removal algorithms , 1992 .
[63] Stochastic Relaxation , 2014, Computer Vision, A Reference Guide.
[64] Heinz H. Bauschke,et al. Fixed-Point Algorithms for Inverse Problems in Science and Engineering , 2011, Springer Optimization and Its Applications.
[65] Om P. Agrawal,et al. Fractional variational calculus in terms of Riesz fractional derivatives , 2007 .
[66] P. Lions,et al. Image recovery via total variation minimization and related problems , 1997 .
[67] Xavier Bresson,et al. Fast Global Minimization of the Active Contour/Snake Model , 2007, Journal of Mathematical Imaging and Vision.
[68] I. Podlubny. Matrix Approach to Discrete Fractional Calculus , 2000 .
[69] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[70] Ke Chen,et al. An Iterative Lagrange Multiplier Method for Constrained Total-Variation-Based Image Denoising , 2012, SIAM J. Numer. Anal..
[71] Jan Modersitzki,et al. Numerical Methods for Image Registration , 2004 .
[72] Tony F. Chan,et al. Image Denoising Using Mean Curvature of Image Surface , 2012, SIAM J. Imaging Sci..
[73] Shubhangi N. Ghate,et al. AN ALGORITHM OF TOTAL VARIATION FOR IMAGE INPAINTING , 2012 .
[74] Y. Meyer,et al. Image decompositions using bounded variation and generalized homogeneous Besov spaces , 2007 .
[75] Y. Zhang,et al. A Class of Fractional-Order Variational Image Inpainting Models , 2012 .
[76] L. Evans. Measure theory and fine properties of functions , 1992 .
[77] M. Nikolova. An Algorithm for Total Variation Minimization and Applications , 2004 .
[78] Chang,et al. A Compound Algorithm of Denoising Using Second-Order and Fourth-Order Partial Differential Equations , 2009 .
[79] Delfim F. M. Torres,et al. Necessary and sufficient conditions for the fractional calculus of variations with Caputo derivatives , 2010, 1007.2937.
[80] Chi-Wang Shu,et al. Shock Capturing, Level Sets and PDE Based Methods in Computer Vision and Image Processing: A Review , 2003 .
[81] C. Vogel,et al. Analysis of bounded variation penalty methods for ill-posed problems , 1994 .
[82] Antonin Chambolle,et al. A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging , 2011, Journal of Mathematical Imaging and Vision.
[83] Andy M. Yip,et al. Simultaneous total variation image inpainting and blind deconvolution , 2005, Int. J. Imaging Syst. Technol..
[84] Horst Bischof,et al. A Duality Based Algorithm for TV- L 1-Optical-Flow Image Registration , 2007, MICCAI.
[85] Om P. Agrawal,et al. Formulation of Euler–Lagrange equations for fractional variational problems , 2002 .
[86] Hong Wang,et al. Fast solution methods for space-fractional diffusion equations , 2014, J. Comput. Appl. Math..