A Two-Stage Image Segmentation Method Using a Convex Variant of the Mumford-Shah Model and Thresholding
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[1] Tom Goldstein,et al. The Split Bregman Method for L1-Regularized Problems , 2009, SIAM J. Imaging Sci..
[2] L. Ljung,et al. Just Relax and Come Clustering! : A Convexification of k-Means Clustering , 2011 .
[3] J. A. Hartigan,et al. A k-means clustering algorithm , 1979 .
[4] Tony F. Chan,et al. Unsupervised Multiphase Segmentation: A Phase Balancing Model , 2010, IEEE Transactions on Image Processing.
[5] M. Morini,et al. Mumford–Shah Functional as Γ-Limit of Discrete Perona–Malik Energies , 2003 .
[6] J. Morel,et al. A multiscale algorithm for image segmentation by variational method , 1994 .
[7] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[8] Mostafa Kaveh,et al. Fourth-order partial differential equations for noise removal , 2000, IEEE Trans. Image Process..
[9] M. Ng,et al. Alternating minimization method for total variation based wavelet shrinkage model , 2010 .
[10] D.M. Mount,et al. An Efficient k-Means Clustering Algorithm: Analysis and Implementation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[11] Xue-Cheng Tai,et al. A Continuous Max-Flow Approach to Potts Model , 2010, ECCV.
[12] Anthony J. Yezzi,et al. Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification , 2001, IEEE Trans. Image Process..
[13] Christopher V. Alvino,et al. Reformulating and Optimizing the Mumford-Shah Functional on a Graph - A Faster, Lower Energy Solution , 2008, ECCV.
[14] Antonin Chambolle,et al. Image Segmentation by Variational Methods: Mumford and Shah Functional and the Discrete Approximations , 1995, SIAM J. Appl. Math..
[15] Karl Kunisch,et al. Total Generalized Variation , 2010, SIAM J. Imaging Sci..
[16] Bingsheng He,et al. Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective , 2012, SIAM J. Imaging Sci..
[17] Michael K. Ng,et al. A Multiphase Image Segmentation Method Based on Fuzzy Region Competition , 2010, SIAM J. Imaging Sci..
[18] Luigi Ambrosio,et al. ON THE APPROXIMATION OF FREE DISCONTINUITY PROBLEMS , 1992 .
[19] Antonin Chambolle,et al. A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging , 2011, Journal of Mathematical Imaging and Vision.
[20] S. Osher,et al. Motion of multiple junctions: a level set approach , 1994 .
[21] Massimo Gobbino. Finite Difference Approximation of the Mumford-Shah Functional , 1998 .
[22] Mila Nikolova,et al. Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models , 2006, SIAM J. Appl. Math..
[23] L. Ambrosio,et al. Approximation of functional depending on jumps by elliptic functional via t-convergence , 1990 .
[24] Tony F. Chan,et al. A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model , 2002, International Journal of Computer Vision.
[25] 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..
[26] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[27] L. Rudin,et al. Nonlinear total variation based noise removal algorithms , 1992 .
[28] A. Chambolle,et al. Discrete approximation of the Mumford-Shah functional in dimension two , 1999, ESAIM: Mathematical Modelling and Numerical Analysis.
[29] Tony F. Chan,et al. High-Order Total Variation-Based Image Restoration , 2000, SIAM J. Sci. Comput..
[30] Tony F. Chan,et al. Mumford and Shah Model and Its Applications to Image Segmentation and Image Restoration , 2015, Handbook of Mathematical Methods in Imaging.
[31] D. Mumford,et al. Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .
[32] S. Esedoglu,et al. Threshold dynamics for the piecewise constant Mumford-Shah functional , 2006 .
[33] Daniel Cremers,et al. A convex relaxation approach for computing minimal partitions , 2009, CVPR.
[34] Serena Morigi,et al. Segmentation of 3D Tubular Structures by a PDE-Based Anisotropic Diffusion Model , 2008, MMCS.
[35] Xavier Bresson,et al. Fast Global Minimization of the Active Contour/Snake Model , 2007, Journal of Mathematical Imaging and Vision.
[36] Jack Xin,et al. Diffusion-Generated Motion by Mean Curvature for Filaments , 2001, J. Nonlinear Sci..
[37] Chunming Li,et al. Multiphase Soft Segmentation with Total Variation and H1 Regularization , 2010, Journal of Mathematical Imaging and Vision.
[38] Tony F. Chan,et al. Active contours without edges , 2001, IEEE Trans. Image Process..
[39] Raymond H. Chan,et al. Vessel Segmentation in Medical Imaging Using a Tight-Frame-Based Algorithm , 2011, SIAM J. Imaging Sci..
[40] Xuecheng Tai,et al. Simultaneous Convex Optimization of Regions and Region Parameters in Image Segmentation Models , 2013, Innovations for Shape Analysis, Models and Algorithms.
[41] Xue-Cheng Tai,et al. A binary level set model and some applications to Mumford-Shah image segmentation , 2006, IEEE Transactions on Image Processing.
[42] Raymond H. Chan,et al. Conjugate Gradient Methods for Toeplitz Systems , 1996, SIAM Rev..
[43] Christoph Schnörr,et al. Continuous Multiclass Labeling Approaches and Algorithms , 2011, SIAM J. Imaging Sci..
[44] Aichi Chien,et al. Frame based segmentation for medical images , 2011 .
[45] Daniel Cremers,et al. An algorithm for minimizing the Mumford-Shah functional , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[46] José M. Bioucas-Dias,et al. Restoration of Poissonian Images Using Alternating Direction Optimization , 2010, IEEE Transactions on Image Processing.
[47] G. David,et al. Singular Sets of Minimizers for the Mumford-Shah Functional , 2005 .
[48] A. Chambolle. FINITE-DIFFERENCES DISCRETIZATIONS OF THE MUMFORD-SHAH FUNCTIONAL , 1999 .
[49] Xue-Cheng Tai,et al. A study on continuous max-flow and min-cut approaches , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[50] Raymond H. Chan,et al. Framelet-Based Algorithm for Segmentation of Tubular Structures , 2011, SSVM.
[51] I. Ekeland,et al. Convex analysis and variational problems , 1976 .
[52] Gabriele Steidl,et al. Segmentation of images with separating layers by fuzzy c-means and convex optimization , 2012, J. Vis. Commun. Image Represent..
[53] OsherStanley,et al. Nonlinear total variation based noise removal algorithms , 1992 .
[54] G. M.,et al. Partial Differential Equations I , 2023, Applied Mathematical Sciences.