EPFL | Biomedical Imaging Group | Hessian Regularization

A Projected Gradient Algorithm for Image Restoration Under Hessian Matrix-Norm Regularization

S. Lefkimmiatis, M. Unser

Proceedings of the 2012 Nineteenth IEEE International Conference on Image Processing (ICIP'12), Orlando FL, USA, September 30-October 3, 2012, pp. 3029-3032.

We have recently introduced a class of non-quadratic Hessian-based regularizers as a higher-order extension of the total variation (TV) functional. These regularizers retain some of the most favorable properties of TV while they can effectively deal with the staircase effect that is commonly met in TV-based reconstructions. In this work we propose a novel gradient-based algorithm for the efficient minimization of these functionals under convex constraints. Furthermore, we validate the overall proposed regularization framework for the problem of image deblurring under additive Gaussian noise.

@INPROCEEDINGS(http://bigwww.epfl.ch/publications/lefkimmiatis1203.html,
AUTHOR="Lefkimmiatis, S. and Unser, M.",
TITLE="A Projected Gradient Algorithm for Image Restoration Under
	{H}essian Matrix-Norm Regularization",
BOOKTITLE="Proceedings of the 2012 Nineteenth {IEEE} International
	Conference on Image Processing ({ICIP'12})",
YEAR="2012",
editor="",
volume="",
series="",
pages="3029--3032",
address="Orlando FL, USA",
month="September 30-October 3,",
organization="",
publisher="",
note="")

© 2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.