@article{36799970810549fea41df95c7d46afb9,
title = "Total Variation Structured Total Least Squares Method for Image Restoration",
abstract = "In this paper, we study the total variation structured total least squares method for image restoration. In the image restoration problem, the point spread function is corrupted by errors. In the model, we study the objective function by minimizing two variables: the restored image and the estimated error of the point spread function. The proposed objective function consists of the data-fitting term containing these two variables, the magnitude of error and the total variation regularization of the restored image. By making use of the structure of the objective function, an efficient alternating minimization scheme is developed to solve the proposed model. Numerical examples are also presented to demonstrate the effectiveness of the proposed model and the efficiency of the numerical scheme.",
keywords = "Alternating minimization, Image restoration, Regularization, Structured total least squares, Total variation",
author = "Zhao, {Xi Le} and Wei Wang and Zeng, {Tie Yong} and Huang, {Ting Zhu} and Ng, {Michael K.}",
note = "Funding information: ^Department of Mathematics, Tongji University, Shanghai, China (weiwamng@163.com). This author{\textquoteright}s research was supported by the National Natural Science Foundation of China (11201341) and China Postdoctoral Science Foundation funded project (2012M511126 and 2013T60459). ^School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, People{\textquoteright}s Republic of China (tingzhuhuang@126.com). This author{\textquoteright}s research was supported by 973 Program (2013CB329404), NSFC (61170311, 61370147), Chinese Universities Specialized Research Fund for the Doctoral Program (20110185 110020), Sichuan Province Scientific and Technical Research Project (2012GZX0080). 丨丨 Corresponding author. Centre for Mathematical Imaging and Vision, and Department of Mathematics, Hong Kong Baptist University, Kowloon, Hong Kong (mng@math.hkbu.edu.hk). This author{\textquoteright}s research was supported by RGC GRF Grant 202013 and HKBU FRG Grant FRG/12-13/065. Publisher copyright: {\textcopyright} 2013 Society for Industrial and Applied Mathematics",
year = "2013",
month = dec,
day = "5",
doi = "10.1137/130915406",
language = "English",
volume = "35",
pages = "B1304--B1320",
journal = "SIAM Journal of Scientific Computing",
issn = "1064-8275",
publisher = "Society for Industrial and Applied Mathematics (SIAM)",
number = "6",
}