%0 Journal Article %1 doi:10.1137/110850591 %A Lee, G. %A Fu, H. %A Barlow, J. %D 2013 %J SIAM Journal on Scientific Computing %K Tikhonov %N 1 %P B275-B290 %R 10.1137/110850591 %T Fast High-Resolution Image Reconstruction Using Tikhonov Regularization Based Total Least Squares %V 35 %X The solution of an ill-conditioned total least squares (TLS) problem from high-resolution imaging by the regularization approach of Golub, Hansen, and O'Leary SIAM J. Matrix Anal. Appl., 21 (2000), pp. 185--194 is considered. This work solves the regularized TLS problem as a system of nonlinear equations in the two regularization parameters. Since the Jacobian of the system can be computed inexpensively, the approach is based upon Newton's method. From experimental results, the algorithm produces a fast computation of the solution of the high-resolution image reconstruction problem.

@article{doi:10.1137/110850591, abstract = {The solution of an ill-conditioned total least squares (TLS) problem from high-resolution imaging by the regularization approach of Golub, Hansen, and O'Leary [SIAM J. Matrix Anal. Appl., 21 (2000), pp. 185--194] is considered. This work solves the regularized TLS problem as a system of nonlinear equations in the two regularization parameters. Since the Jacobian of the system can be computed inexpensively, the approach is based upon Newton's method. From experimental results, the algorithm produces a fast computation of the solution of the high-resolution image reconstruction problem.}, added-at = {2013-05-05T23:58:24.000+0200}, author = {Lee, G. and Fu, H. and Barlow, J.}, biburl = {https://www.bibsonomy.org/bibtex/2efaa5153740a76fb7852bb4e93a0163b/ytyoun}, doi = {10.1137/110850591}, interhash = {de17861fd796e2c66e81b7af4510948f}, intrahash = {efaa5153740a76fb7852bb4e93a0163b}, journal = {SIAM Journal on Scientific Computing}, keywords = {Tikhonov}, number = 1, pages = {B275-B290}, timestamp = {2013-05-05T23:58:25.000+0200}, title = {Fast High-Resolution Image Reconstruction Using Tikhonov Regularization Based Total Least Squares}, volume = 35, year = 2013 }