Daniele Graziani

Post-Doctorant

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Dernières publications dans le projet Ariana :

A new variational method for preserving point-like and curve-like singularities in 2d images. D. Graziani et L. Blanc-Féraud et G. Aubert. Dans Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, Czech Republic, mai 2011. Mots-clés : Convex optimization, nesterov scheme, laplacian operator. @INPROCEEDINGS{ICASSP_Graziani11, author = {Graziani, D. and Blanc-Féraud, L. and Aubert, G.}, title = {A new variational method for preserving point-like and curve-like singularities in 2d images}, year = {2011}, month = {mai}, booktitle = {Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, address = {Prague, Czech Republic}, url = {http://hal.inria.fr/inria-00592603/fr/}, keyword = {Convex optimization, nesterov scheme, laplacian operator} } 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 becomes singular at points and curves. Then we propose to restore these singularities by introducing suitable regularization involving the l-1-norm of the Laplacian operator. Results are shown on synthetic an real data. A formal Gamma-convergence approach for the detection of points in 2-D biological images. D. Graziani et G. Aubert et L. Blanc-Féraud. SIAM Journal on Imaging Sciences, 3(3): pages 578-594, septembre 2010. Mots-clés : points detection, curvature-depending functionals, divergence-measure fields. @ARTICLE{2, author = {Graziani, D. and Aubert, G. and Blanc-Féraud, L.}, title = {A formal Gamma-convergence approach for the detection of points in 2-D biological images}, year = {2010}, month = {septembre}, journal = {SIAM Journal on Imaging Sciences}, volume = {3}, number = {3}, pages = {578-594}, url = {http://hal.inria.fr/inria-00503152/}, keyword = {points detection, curvature-depending functionals, divergence-measure fields} } Abstract : We propose a new variational model to locate points in 2-dimensional biological images. To this purpose we introduce a suitable functional whose minimizers are given by the points we want to detect. In order to provide numerical experiments we replace this energy with a sequence of a more treatable functionals by means of the notion of Gamma-convergence. Variational approximation for detecting point-like target problems. D. Graziani et G. Aubert. COCV: Esaim Control Optimization and Calculus of Variations DOI: 10.1051/cocv/2010029, août 2010. Mots-clés : points detection, Images biologiques, divergence-measure fields. @ARTICLE{COCV2010, author = {Graziani, D. and Aubert, G.}, title = {Variational approximation for detecting point-like target problems}, year = {2010}, month = {août}, journal = {COCV: Esaim Control Optimization and Calculus of Variations DOI: 10.1051/cocv/2010029}, url = {http://dx.doi.org/10.1051/cocv/2010029}, keyword = {points detection, Images biologiques, divergence-measure fields} } Abstract : The aim of this paper is to provide a rigorous variational formulation for the detection of points in 2-d biological images. To this purpose we introduce a new functional whose minimizers give the points we want to detect. Then we define an approximating sequence of functionals for which we prove the Γ-convergence to the initial one.

Liste complète des publications dans le projet Ariana