An Edge-Preserving Multilevel Method for Deblurring, Denoising, and Segmentation

Authors:
Serena Morigi;Lothar Reichel;Fiorella Sgallari
Affiliations:
Dept. of Mathematics-CIRAM, University of Bologna, Bologna, Italy;Dept. of Mathematical Sciences, Kent State University, Kent, USA OH 44242;Dept. of Mathematics-CIRAM, University of Bologna, Bologna, Italy
Venue:
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Year:
2009

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Abstract

We present a fast edge-preserving cascadic multilevel image restoration method for reducing blur and noise in contaminated images. The method also can be applied to segmentation. Our multilevel method blends linear algebra and partial differential equation techniques. Regularization is achieved by truncated iteration on each level. Prolongation is carried out by nonlinear edge-preserving and noise-reducing operators. A thresholding updating technique is shown to reduce "ringing" artifacts. Our algorithm combines deblurring, denoising, and segmentation within a single framework.