Optimization and Control

[6] A Two-Stage Image Segmentation Method Using a Convex Variant of the Mumford--Shah Model and Thresholding

Xiaohao Cai The Chinese University of Hong Kong Raymond Chan The Chinese University of Hong Kong Tieyong Zeng Hong Kong Baptist University

Optimization and Control mathscidoc:1705.27004

SIAM Journal on Imaging Sciences, 6, (1), 368-390, 2013
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[7] Minimization and parameter estimation for seminorm regularization models with I -divergence constraints

T Teuber University of Kaiserslautern G Steidl University of Kaiserslautern Raymond Chan The Chinese University of Hong Kong

Optimization and Control Statistics Theory and Methods mathscidoc:1705.27003

Inverse Problems, 29, (3), 2013
[ Download ] [ 2017-05-30 13:25:15 uploaded by yauawardadmin ] [ 145 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[8] Constrained Total Variation Deblurring Models and Fast Algorithms Based on Alternating Direction Method of Multipliers

Raymond H. Chan The Chinese University of Hong Kong Min Tao Nanjing University of Posts and Telecommunications Xiaoming Yuan Hong Kong Baptist University

Optimization and Control mathscidoc:1705.27002

SIAM Journal on Imaging Sciences, 6, (1), 680-697, 2013
[ Download ] [ 2017-05-30 12:56:22 uploaded by yauawardadmin ] [ 166 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[9] Inertial Proximal ADMM for Linearly Constrained Separable Convex Optimization

Caihua Chen Nanjing University Raymond H. Chan The Chinese University of Hong Kong Shiqian Ma The Chinese University of Hong Kong Junfeng Yang Nanjing University

Optimization and Control Convex and Discrete Geometry mathscidoc:1705.27001

SIAM Journal on Imaging Sciences, 8, (4), 2239-2267, 2015
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[10] A Nuclear-norm Model for Multi-Frame Super-Resolution Reconstruction from Video Clips

Rui Zhao The Chinese University of Hong Kong Raymond H. Chan The Chinese University of Hong Kong

Optimization and Control mathscidoc:1704.27001

[ Download ] [ 2017-04-25 17:40:49 uploaded by raydrs ] [ 213 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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