@article {15760,
	title = {Implementation of the regularized structured total least squares algorithms for blind image deblurring},
	journal = {Linear Algebra and its Applications},
	volume = {391},
	year = {2004},
	month = {2004/11/01/},
	pages = {203 - 221},
	abstract = {The structured total least squares (STLS) problem has been introduced to handle problems involving structured matrices corrupted by noise. Often the problem is ill-posed. Recently, regularization has been proposed in the STLS framework to solve ill-posed blind deconvolution problems encountered in image deblurring when both the image and the blurring function have uncertainty. The kernel of the regularized STLS (RSTLS) problem is a least squares problem involving Block{\textendash}Toeplitz{\textendash}Toeplitz{\textendash}Block matrices.In this paper an algorithm is described to solve this problem, based on a particular implementation of the generalized Schur Algorithm (GSA). It is shown that this new implementation improves the computational efficiency of the straightforward implementation of GSA from O(N2.5) to O(N2), where N is the number of pixels in the image.
},
	keywords = {Block Toeplitz matrix, Displacement rank, Generalized Schur algorithm, Image deblurring, Structured total least squares, Tikhonov regularization},
	isbn = {0024-3795},
	doi = {10.1016/j.laa.2004.07.006},
	url = {http://www.sciencedirect.com/science/article/pii/S0024379504003362},
	author = {Mastronardi,N. and Lemmerling,P. and Kalsi,A. and O{\textquoteright}Leary,D. P and Huffel,S. Van}
}
