TY - JOUR
T1 - Blind deconvolution using generalized cross-validation approach to regularization parameter estimation
AU - Liao, Haiyong
AU - NG, Kwok Po
N1 - Funding Information:
Manuscript received December 16, 2009; revised June 14, 2010; accepted August 27, 2010. Date of publication September 07, 2010; date of current version February 18, 2011. This work was supported in part by grants from the Hong Kong Research Grant Council and Hong Kong Baptist University Faculty Research rant. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Yongyi Yang.
PY - 2011/3
Y1 - 2011/3
N2 - In this paper, we propose and present an algorithm for total variation (TV)-based blind deconvolution. Both the unknown image and blur can be estimated within an alternating minimization framework. With the generalized cross-validation (GCV) method, the regularization parameters associated with the unknown image and blur can be updated in alternating minimization steps. Experimental results confirm that the performance of the proposed algorithm is better than variational Bayesian blind deconvolution algorithms with Student's-t priors or a total variation prior.
AB - In this paper, we propose and present an algorithm for total variation (TV)-based blind deconvolution. Both the unknown image and blur can be estimated within an alternating minimization framework. With the generalized cross-validation (GCV) method, the regularization parameters associated with the unknown image and blur can be updated in alternating minimization steps. Experimental results confirm that the performance of the proposed algorithm is better than variational Bayesian blind deconvolution algorithms with Student's-t priors or a total variation prior.
KW - Alternating minimization
KW - blind deconvolution
KW - generalized cross validation (GCV)
KW - regularization parameters
KW - total variation (TV)
UR - http://www.scopus.com/inward/record.url?scp=79951838700&partnerID=8YFLogxK
U2 - 10.1109/TIP.2010.2073474
DO - 10.1109/TIP.2010.2073474
M3 - Article
AN - SCOPUS:79951838700
VL - 20
SP - 670
EP - 680
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
SN - 1057-7149
IS - 3
M1 - 5565466
ER -