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[Other resource] Fast_Global_Minimization_Active_Contour DL : 0: Author: Xavier Bresson (％ Last version: Aug 3, 2008 ％ For more information: X. Bresson and T.F. Chan, \"Fast Minimization of the Vectorial Total Variation Norm and Applications to Color Image Processing\", CAM Report 07-25
Update : 2008-10-13 Size : 53.22kb Publisher : 代松
[Other resource] Fast_Color_Denoising_ROF DL : 0: Name: gmac = global minimization of the active contour model ％ Description: see paper \"Fast Global Minimization of the Active Contour/Snake Model\" in JMIV07 ％ Author: Xavier Bresson (xbresson@math.ucla.edu) ％ Lastest version: 07-09-21
Update : 2008-10-13 Size : 53.67kb Publisher : 代松
[matlab] TVAL3 DL : 0: %TVDENOISE Total variation grayscale and color image denoising % u = TVDENOISE(f,lambda) denoises the input image f. The smaller % the parameter lambda, the stronger the denoising. % % The output u approximately minimizes the Rudin-Osher-Fatemi (ROF) % denoising model % % Min TV(u) + lambda/2 || f - u ||^2_2, % u % % where TV(u) is the total variation of u. If f is a color image (or any % array where size(f,3) > 1), the vectorial TV model is used, % % Min VTV(u) + lambda/2 || f - u ||^2_2. % u % % TVDENOISE(...,Tol) specifies the stopping tolerance (default 1e-2). % % The minimization is solved using Chambolle's method, % A. Chambolle, "An Algorithm for Total Variation Minimization and % Applications," J. Math. Imaging and Vision 20 (1-2): 89-97, 2004. % When f is a color image, the minimization is solved by a generalization % of Chambolle's method, % X. Bresson and T.F. Chan, "Fast Minimization of the Vectorial Total % Variation Norm and Applications to Color Image Processing", UCLA CAM % Report 07-25.
Update : 2011-04-11 Size : 1.4kb Publisher : li123kai@126.com
[2D Graphic] Fast_Global_Minimization_Active_Contour DL : 0: Author: Xavier Bresson (％ Last version: Aug 3, 2008 ％ For more information: X. Bresson and T.F. Chan, "Fast Minimization of the Vectorial Total Variation Norm and Applications to Color Image Processing", CAM Report 07-25-Author: Xavier Bresson ( Last version: Aug 3, 2008 For more information: X. Bresson and TF Chan, Fast Minimization of the Vectorial Total Variation Norm and Applications to Color ImageProcessing , CAM Report 07-25
Update : 2025-04-04 Size : 53kb Publisher : 代松
[2D Graphic] Fast_Color_Denoising_ROF DL : 0: Name: gmac = global minimization of the active contour model ％ Description: see paper "Fast Global Minimization of the Active Contour/Snake Model" in JMIV07 ％ Author: Xavier Bresson (xbresson@math.ucla.edu) ％ Lastest version: 07-09-21-Name: gmac = global minimization of the active contour model Description: see paper Fast Global Minimization of the Active Contour/Snake Model in JMIV07 Author: Xavier Bresson (xbresson@math.ucla.edu) Lastest version: 07-- 09-21
Update : 2025-04-04 Size : 54kb Publisher : 代松
[Graph program] histgramTest DL : 0: 本程序计算局部窗口的累积直方图，可用于驱动水平集和纹理分割- in this test program, we calculate the cumulative histogram in a local window centered at each pixel,this local cumulative histogram can be used to drive the level set for image and texture segmentation. Author: Associate Prof. Yuanquan Wang, Affiliation: Tianjin Key Lab of Intelligent Computing and Novel Software Technology, School of Computer Science, Tianjin University of Technology, Tianjin 300191, China 01/20/2008 Reference: 1. Tony Chan, Selim Esedoglu, and Kangyu Ni, Histogram Based Segmentation Using Wasserstein Distances, SSVM 2007, LNCS 4485, pp. 697–708, 2007. 2. Kangyu Ni, Xavier Bresson, Tony Chan, Selim Esedog, Local Histogram based Segmentation using the Wasserstein Distance, at: www.math.lsa.umich.edu/~esedoglu/Papers_Preprints/chan_esedoglu_ni.pdf or at :ftp://ftp.math.ucla.edu/pub/camreport/cam08-47.pdf
Update : 2025-04-04 Size : 2kb Publisher : 方可
[2D Graphic] segment DL : 0: 代码的sbseg’是一个非常快速的图像分割，由陈，esedoglu最初提出的变分模型的实现，以及Nikolova。分割模型和它的分裂Bregman方法数值解是在分裂Bregman方法本文几何应用描述：重建，分割和表面由汤姆德斯坦，沙维尔布列松，和斯坦利Osher。-The code ‘sbseg’ is an extremely fast implementation of the variational model for image segmentation originally proposed by Chan, Esedoglu, and Nikolova. The segmentation model and it’s numerical solution by the Split Bregman method are described in the paper Geometric Applications of the Split Bregman Method: Segmentation and Surface Reconstruction, by Tom Goldstein, Xavier Bresson, and Stanley Osher.
Update : 2025-04-04 Size : 4kb Publisher : wangyouquan