DocumentCode :
2154110
Title :
A new variational method for preserving point-like and curve-like singularities in 2-D images
Author :
Graziani, Daniele ; Blanc-Féraud, Laure ; Aubert, Gilles
Author_Institution :
ARIANA CNRS/INRIA/UNSA Sophia Antipolis, Sophia Antipolis, France
fYear :
2011
fDate :
22-27 May 2011
Firstpage :
937
Lastpage :
940
Abstract :
We propose a new variational method to restore point-like and curve-like singularities in 2-D images. As points and open curves are fine structures, they are difficult to restore by means of first order derivative operators computed in the noisy image. In this paper we propose to use the Laplacian operator of the observed intensity, since it be comes singular at points and curves. Then we propose to restore these singularities by introducing suitable regularization involving the M-norm of the Laplacian operator. Results are shown on synthetic an real data.
Keywords :
image restoration; variational techniques; 2D image restoration; Laplacian operator; curve-like singularity; first order derivative operator; l1-norm operator; noisy image; open curve; point-like singularity; variational method; Biomedical imaging; Image restoration; Laplace equations; Minimization; Noise measurement; PSNR; Nesterov scheme; image processing; l1-minimization; laplacian operator; non smooth convex optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague
ISSN :
1520-6149
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2011.5946559
Filename :
5946559
Link To Document :
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