Novel Iterative Truncated Total Least Squares Algorithm for Image Restoration

Lei Zhang; Yue Yun Cao; Zi Chun Yang

doi:10.4028/www.scientific.net/AMM.401-403.1397

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 401-403Novel Iterative Truncated Total Least Squares...

Novel Iterative Truncated Total Least Squares Algorithm for Image Restoration

Abstract:

Image restoration is a typical ill-posed inverse problem, which can be solved by a successful total least squares (TLS) method when not only the observation but the system matrix is also contaminated by addition noise. Considering the image restoration is a large-scale problem in general, project the TLS problem onto a subspace defined by a Lanczos bidiagonalization algorithm, and then the Truncated TLS method is applied on the subspace. Therefore, a novel iterative TTLS method, involving appropriate the choice of truncation parameter, is proposed. Finally, an Image reconstruction example is given to illustrate the effectiveness and robustness of proposed algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 401-403)

Pages:

1397-1400

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.401-403.1397

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Online since:

September 2013

Authors:

Lei Zhang, Yue Yun Cao, Zi Chun Yang

Keywords:

Discrete Ill-Posed Problems, Image Restoration, Lanczos, Regularization, Truncated Total Least Squares

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