The solution of image restoration problems usually requires the use of regularization strategies. The L-curve criterium is a popular heuristic tool for choosing good regularized solutions, when the data noise norm is not a priori known. In this work, we propose replacing the original image restoration problem with a noise-independent equality constrained one and solving it by an iterative Lagrange method. The sequence of the computed iterates defines a discrete L-shaped curve. By numerical results, we show that good regularized solutions correspond with the corner of this curve.
A Lagrange method based L-curve for image restoration / G Landi. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6596. - ELETTRONICO. - 464:(2013), pp. 012011-012011. (Intervento presentato al convegno 3rd International Workshop on New Computational Methods for Inverse Problems, NCMIP 2013 tenutosi a Cachan; France nel 22 May 2013) [10.1088/1742-6596/464/1/012011].
A Lagrange method based L-curve for image restoration
LANDI, GERMANA
2013
Abstract
The solution of image restoration problems usually requires the use of regularization strategies. The L-curve criterium is a popular heuristic tool for choosing good regularized solutions, when the data noise norm is not a priori known. In this work, we propose replacing the original image restoration problem with a noise-independent equality constrained one and solving it by an iterative Lagrange method. The sequence of the computed iterates defines a discrete L-shaped curve. By numerical results, we show that good regularized solutions correspond with the corner of this curve.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
