TY - JOUR
T1 - Variational Approach for Restoring Blurred Images with Cauchy Noise
AU - Sciacchitano, Federica
AU - Dong, Yiqiu
AU - Zeng, Tieyong
N1 - Funding information:
Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark ([email protected], [email protected]). The work of the second author was supported by Advanced Grant 291405 from the European Research Council.
^Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong ([email protected]). The work of this author was partially supported by NSFC 11271049, RGC 211911, 12302714, and RFGs of HKBU.
Publisher copyright:
© 2015, Society for Industrial and Applied Mathematics
PY - 2015/9/17
Y1 - 2015/9/17
N2 - The restoration of images degraded by blurring and noise is one of the most important tasks in image processing. In this paper, based on the total variation (TV) we propose a new variational method for recovering images degraded by Cauchy noise and blurring. In order to obtain a strictly convex model, we add a quadratic penalty term, which guarantees the uniqueness of the solution. Due to the convexity of our model, the primal dual algorithm is employed to solve the minimization problem. Experimental results show the effectiveness of the proposed method for simultaneously deblurring and denoising images corrupted by Cauchy noise. Comparison with other existing and well-known methods is provided as well.
AB - The restoration of images degraded by blurring and noise is one of the most important tasks in image processing. In this paper, based on the total variation (TV) we propose a new variational method for recovering images degraded by Cauchy noise and blurring. In order to obtain a strictly convex model, we add a quadratic penalty term, which guarantees the uniqueness of the solution. Due to the convexity of our model, the primal dual algorithm is employed to solve the minimization problem. Experimental results show the effectiveness of the proposed method for simultaneously deblurring and denoising images corrupted by Cauchy noise. Comparison with other existing and well-known methods is provided as well.
KW - Cauchy noise
KW - Image deblurring
KW - Image denoising
KW - Primal dual algorithm
KW - Total variation regularization
KW - Variational model
UR - http://www.scopus.com/inward/record.url?scp=84943571510&partnerID=8YFLogxK
U2 - 10.1137/140997816
DO - 10.1137/140997816
M3 - Journal article
AN - SCOPUS:84943571510
SN - 1936-4954
VL - 8
SP - 1894
EP - 1922
JO - SIAM Journal on Imaging Sciences
JF - SIAM Journal on Imaging Sciences
IS - 3
ER -