Publications de 2005

Résultat de la recherche dans la liste des publications :

• 9 Articles
• 2 Thèses de Doctorat et Habilitations
• 13 Articles de conférence
• 10 Rapports de recherche et Rapports techniques
• 1 Article de collection ou Chapitre de livre

nouvelle recherche | bibtex

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9 Articles

1 - Detecting codimension-two objects in an image with Ginzburg-Landau models. G. Aubert et J.F. Aujol et L. Blanc-Féraud. International Journal of Computer Vision, 65(1-2): pages 29-42, novembre 2005. Mots-clés : Modele de Ginzburg-Landau, Detection de points, Segmentation, PDE, Images biologiques, Images SAR. @ARTICLE{laure-ijcv05, author = {Aubert, G. and Aujol, J.F. and Blanc-Féraud, L.}, title = {Detecting codimension-two objects in an image with Ginzburg-Landau models}, year = {2005}, month = {novembre}, journal = {International Journal of Computer Vision}, volume = {65}, number = {1-2}, pages = {29-42}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/GL_IJCV_5.pdf}, keyword = {Modele de Ginzburg-Landau, Detection de points, Segmentation, PDE, Images biologiques, Images SAR} } Abstract : In this paper, we propose a new mathematical model for detecting in an image singularities of codimension greater than or equal to two. This means we want to detect points in a 2-D image or points and curves in a 3-D image. We drew one's inspiration from Ginzburg-Landau (G-L) models which have proved their efficiency for modeling many phenomena in physics. We introduce the model, state its mathematical properties and give some experimental results demonstrating its capability in image processing.

2 - Point Processes for Unsupervised Line Network Extraction in Remote Sensing. C. Lacoste et X. Descombes et J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 27(10): pages 1568-1579, octobre 2005. @ARTICLE{lacoste05, author = {Lacoste, C. and Descombes, X. and Zerubia, J.}, title = {Point Processes for Unsupervised Line Network Extraction in Remote Sensing}, year = {2005}, month = {octobre}, journal = {IEEE Trans. Pattern Analysis and Machine Intelligence}, volume = {27}, number = {10}, pages = {1568-1579}, pdf = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=32189&arnumber=1498752&count=18&index=4}, keyword = {} }

3 - Supervised Segmentation of Remote Sensing Images Based on a Tree-Structure MRF Model. G. Poggi et G. Scarpa et J. Zerubia. IEEE Trans. Geoscience and Remote Sensing, 43(8): pages 1901-1911, août 2005. Mots-clés : Classification, Segmentation, Champs de Markov. @ARTICLE{ieeetgrs_05, author = {Poggi, G. and Scarpa, G. and Zerubia, J.}, title = {Supervised Segmentation of Remote Sensing Images Based on a Tree-Structure MRF Model}, year = {2005}, month = {août}, journal = {IEEE Trans. Geoscience and Remote Sensing}, volume = {43}, number = {8}, pages = {1901-1911}, pdf = {http://ieeexplore.ieee.org/iel5/36/32001/01487647.pdf?tp=&arnumber=1487647&isnumber=32001}, keyword = {Classification, Segmentation, Champs de Markov} }

4 - Dual Norms and Image Decomposition Models. J.F. Aujol et A. Chambolle. International Journal of Computer Vision, 63(1): pages 85-104, juin 2005. Mots-clés : Decomposition d'images. @ARTICLE{AujolChambolle, author = {Aujol, J.F. and Chambolle, A.}, title = {Dual Norms and Image Decomposition Models}, year = {2005}, month = {juin}, journal = {International Journal of Computer Vision}, volume = {63}, number = {1}, pages = {85-104}, pdf = {http://link.springer.com/article/10.1007/s11263-005-4948-3}, keyword = {Decomposition d'images} }

5 - Invariant Bayesian estimation on manifolds. I. H. Jermyn. Annals of Statistics, 33(2): pages 583--605, avril 2005. Mots-clés : Estimation bayesienne, MAP, MMSE, Invariant, Metrique, Jeffrey's. @ARTICLE{jermyn_annstat05, author = {Jermyn, I. H.}, title = {Invariant Bayesian estimation on manifolds}, year = {2005}, month = {avril}, journal = {Annals of Statistics}, volume = {33}, number = {2}, pages = {583--605}, url = {http://dx.doi.org/10.1214/009053604000001273}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/jermyn_annstat05.pdf}, keyword = {Estimation bayesienne, MAP, MMSE, Invariant, Metrique, Jeffrey's} } Abstract : A frequent and well-founded criticism of the maximum em a posteriori (MAP) and minimum mean squared error (MMSE) estimates of a continuous parameter param taking values in a differentiable manifold paramspace is that they are not invariant to arbitrary `reparametrizations' of paramspace. This paper clarifies the issues surrounding this problem, by pointing out the difference between coordinate invariance, which is a em sine qua non for a mathematically well-defined problem, and diffeomorphism invariance, which is a substantial issue, and then provides a solution. We first show that the presence of a metric structure on paramspace can be used to define coordinate-invariant MAP and MMSE estimates, and we argue that this is the natural way to proceed. We then discuss the choice of a metric structure on paramspace. By imposing an invariance criterion natural within a Bayesian framework, we show that this choice is essentially unique. It does not necessarily correspond to a choice of coordinates. In cases of complete prior ignorance, when Jeffreys' prior is used, the invariant MAP estimate reduces to the maximum likelihood estimate. The invariant MAP estimate coincides with the minimum message length (MML) estimate, but no discretization or approximation is used in its derivation.

6 - Modeling very Oscillating Signals. Application to Image Processing. G. Aubert et J.F. Aujol. Applied Mathematics and Optimization, 51(2): pages 163--182, mars 2005. @ARTICLE{AujolAubert, author = {Aubert, G. and Aujol, J.F.}, title = {Modeling very Oscillating Signals. Application to Image Processing}, year = {2005}, month = {mars}, journal = {Applied Mathematics and Optimization}, volume = {51}, number = {2}, pages = {163--182}, pdf = {http://link.springer.com/article/10.1007/s00245-004-0812-z}, keyword = {} }

7 - Optimal Partitions, Regularized Solutions, and Application to Image Classification. G. Aubert et J.F. Aujol. Applicable Analysis, 84(1): pages 15--35, janvier 2005. @ARTICLE{AujolAubertclassif, author = {Aubert, G. and Aujol, J.F.}, title = {Optimal Partitions, Regularized Solutions, and Application to Image Classification}, year = {2005}, month = {janvier}, journal = {Applicable Analysis}, volume = {84}, number = {1}, pages = {15--35}, pdf = {http://www.math.u-bordeaux1.fr/~jaujol/HDR/A2.pdf}, keyword = {} }

8 - Image Decomposition into a Bounded Variation Component and an Oscillating Component. J.F. Aujol et G. Aubert et L. Blanc-Féraud et A. Chambolle. Journal of Mathematical Imaging and Vision, 22(1): pages 71--88, janvier 2005. @ARTICLE{BLA05, author = {Aujol, J.F. and Aubert, G. and Blanc-Féraud, L. and Chambolle, A.}, title = {Image Decomposition into a Bounded Variation Component and an Oscillating Component}, year = {2005}, month = {janvier}, journal = {Journal of Mathematical Imaging and Vision}, volume = {22}, number = {1}, pages = {71--88}, pdf = {http://link.springer.com/article/10.1007/s10851-005-4783-8}, keyword = {} }

9 - Modèle Paramétrique pour la Reconstruction Automatique en 3D de Zones Urbaines Denses à partir d'Images Satellitaires Haute Résolution. F. Lafarge et X. Descombes et J. Zerubia et M. Pierrot-Deseilligny. Revue Française de Photogrammétrie et de Télédétection (SFPT), 180: pages 4--12, 2005. Mots-clés : Reconstruction en 3D, Zones urbaines, Approche bayésienne, MCMC, Imagerie satellitaire. Copyright : SFPT @ARTICLE{lafarge_sfpt05, author = {Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, title = {Modèle Paramétrique pour la Reconstruction Automatique en 3D de Zones Urbaines Denses à partir d'Images Satellitaires Haute Résolution}, year = {2005}, journal = {Revue Française de Photogrammétrie et de Télédétection (SFPT)}, volume = {180}, pages = {4--12}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/2005_lafarge_sfpt05.pdf}, keyword = {Reconstruction en 3D, Zones urbaines, Approche bayésienne, MCMC, Imagerie satellitaire} }

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2 Thèses de Doctorat et Habilitations

1 - Constance de largeur et désocclusion dans les images digitales. E. Villéger. Thèse de Doctorat, Universite de Nice Sophia Antipolis, décembre 2005. @PHDTHESIS{villeger_these, author = {Villéger, E.}, title = {Constance de largeur et désocclusion dans les images digitales}, year = {2005}, month = {décembre}, school = {Universite de Nice Sophia Antipolis}, pdf = { http://www-sop.inria.fr/dias/Theses/phd-12.php}, keyword = {} }

2 - Contours actifs d'ordre supérieur et leur application à la détection de linéiques dans des images de télédétection. M. Rochery. Thèse de Doctorat, Universite de Nice Sophia Antipolis, Sophia Antipolis, septembre 2005. Mots-clés : Contour actif, Ordre superieur, Champ de Phase, Reseaux lineiques, Reseaux routiers. @PHDTHESIS{rochery_these, author = {Rochery, M.}, title = {Contours actifs d'ordre supérieur et leur application à la détection de linéiques dans des images de télédétection}, year = {2005}, month = {septembre}, school = {Universite de Nice Sophia Antipolis}, address = {Sophia Antipolis}, pdf = {http://hal.inria.fr/docs/00/04/86/28/PDF/tel-00010631.pdf}, keyword = {Contour actif, Ordre superieur, Champ de Phase, Reseaux lineiques, Reseaux routiers} }

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13 Articles de conférence

1 - Adaptive Simulated Annealing for Energy Minimization Problem in a Marked Point Process Application. G. Perrin et X. Descombes et J. Zerubia. Dans Proc. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), St Augustine, Florida, USA, novembre 2005. Mots-clés : Recuit Simule, Processus ponctuels marques, Geometrie stochastique, Estimation MAP, RJMCMC. Copyright : Springer Verlag @INPROCEEDINGS{perrin_emmcvpr05, author = {Perrin, G. and Descombes, X. and Zerubia, J.}, title = {Adaptive Simulated Annealing for Energy Minimization Problem in a Marked Point Process Application}, year = {2005}, month = {novembre}, booktitle = {Proc. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, address = {St Augustine, Florida, USA}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/perrin_emmcvpr.pdf}, ps = {ftp://ftp-sop.inria.fr/ariana/Articles/perrin_emmcvpr.ps.gz}, keyword = {Recuit Simule, Processus ponctuels marques, Geometrie stochastique, Estimation MAP, RJMCMC} } Abstract : We use marked point processes to detect an unknown number of trees from high resolution aerial images. This is in fact an energy minimization problem, where the energy contains a prior term which takes into account the geometrical properties of the objects, and a data term to match these objects to the image. This stochastic process is simulated via a Reversible Jump Markov Chain Monte Carlo procedure, which embeds a Simulated Annealing scheme to extract the best configuration of objects. We compare here different cooling schedules of the Simulated Annealing algorithm which could provide some good minimization in a short time. We also study some adaptive proposition kernels.

2 - Phase field models and higher-order active contours. M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Computer Vision (ICCV), Beijing, China, octobre 2005. Mots-clés : Contour actif, Ordre superieur, Forme, Reseaux lineiques, Reseaux routiers, Champ de Phase. @INPROCEEDINGS{rochery_iccv05, author = {Rochery, M. and Jermyn, I. H. and Zerubia, J.}, title = {Phase field models and higher-order active contours}, year = {2005}, month = {octobre}, booktitle = {Proc. IEEE International Conference on Computer Vision (ICCV)}, address = {Beijing, China}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/rochery_iccv05.pdf}, keyword = {Contour actif, Ordre superieur, Forme, Reseaux lineiques, Reseaux routiers, Champ de Phase} } Abstract : The representation and modelling of regions is an important topic in computer vision. In this paper, we represent a region via a level set of a `phase field' function. The function is not constrained, eg to be a distance function; nevertheless, phase field energies equivalent to classical active contour energies can be defined. They represent an advantageous alternative to other methods: a linear representation space; ease of implementation (a PDE with no reinitialization); neutral initialization; greater topological freedom. We extend the basic phase field model with terms that reproduce `higher-order active contour' energies, a powerful way of including prior geometric knowledge in the active contour framework via nonlocal interactions between contour points. In addition to the above advantages, the phase field greatly simplifies the analysis and implementation of the higher-order terms. We define a phase field model that favours regions composed of thin arms meeting at junctions, combine this with image terms, and apply the model to the extraction of line networks from remote sensing images.

3 - Détection de feux de forêt à partir d'images satellitaires IRT par analyse statistique d'évènements rares. F. Lafarge et X. Descombes et J. Zerubia et S. Mathieu-Marni. Dans Proc. GRETSI Symposium on Signal and Image Processing, Louvain-la-Neuve, Belgique, septembre 2005. Mots-clés : Évenement rare, Feux de foret, Champs Gaussiens. @INPROCEEDINGS{lafarge_gretsi05, author = {Lafarge, F. and Descombes, X. and Zerubia, J. and Mathieu-Marni, S.}, title = {Détection de feux de forêt à partir d'images satellitaires IRT par analyse statistique d'évènements rares}, year = {2005}, month = {septembre}, booktitle = {Proc. GRETSI Symposium on Signal and Image Processing}, address = {Louvain-la-Neuve, Belgique}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/2005_lafarge_gretsi05.pdf}, keyword = {Évenement rare, Feux de foret, Champs Gaussiens} }

4 - New Higher-order Active Contour Energies for Network Extraction. M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Genoa, Italy, septembre 2005. Mots-clés : Gap closure, Forme, A priori, Ordre superieur, Contour actif. @INPROCEEDINGS{rochery_icip05, author = {Rochery, M. and Jermyn, I. H. and Zerubia, J.}, title = {New Higher-order Active Contour Energies for Network Extraction}, year = {2005}, month = {septembre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Genoa, Italy}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/rochery_icip05.pdf}, keyword = {Gap closure, Forme, A priori, Ordre superieur, Contour actif} } Abstract : Using the framework of higher-order active contours, we present a new quadratic em continuation energy for the extraction of line networks (e.g. road, hydrographic, vascular) in the presence of occlusions. Occlusions create gaps in the data that frequently translate to gaps in the extracted network. The new energy penalizes earby opposing extremities of the network, and thus favours the closure of the gaps created by occlusions. Nearby opposing extremities are identified using a sophisticated interaction between pairs of points on the contour. This new model allows the extraction of fully connected networks, even though occlusions violate common assumptions about the homogeneity of the interior, and high contrast with the exterior, of the network. We present experimental results on real aerial images that demonstrate the effectiveness of the new model for network extraction tasks.

5 - Extraction of hydrographic networks from satellite images using a hierarchical model within a stochastic geometry framework. C. Lacoste et X. Descombes et J. Zerubia et N. Baghdadi. Dans Proc. European Signal Processing Conference (EUSIPCO), Antalya, Turkey, septembre 2005. @INPROCEEDINGS{lacoste_eusipco05, author = {Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, title = {Extraction of hydrographic networks from satellite images using a hierarchical model within a stochastic geometry framework}, year = {2005}, month = {septembre}, booktitle = {Proc. European Signal Processing Conference (EUSIPCO)}, address = {Antalya, Turkey}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7078007}, keyword = {} }

6 - Application of ant colony optimization to image classification using a Markov model withnonstationary neighborhoods. S. Le Hegarat-Mascle et A. Kallel et X. Descombes. Dans Proc. SPIE Symposium on Remote Sensing, Vol. 5982, Bruges, Belgium, septembre 2005. @INPROCEEDINGS{mascle_spie_05, author = {Le Hegarat-Mascle, S. and Kallel, A. and Descombes, X.}, title = {Application of ant colony optimization to image classification using a Markov model withnonstationary neighborhoods}, year = {2005}, month = {septembre}, booktitle = {Proc. SPIE Symposium on Remote Sensing}, volume = {5982}, address = {Bruges, Belgium}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=879756}, keyword = {} }

7 - Textural Kernel for SVM Classification in Remote Sensing : Application to Forest Fire Detection and Urban Area Extraction. F. Lafarge et X. Descombes et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Genoa, Italy, septembre 2005. Mots-clés : Support Vector Machines, Base d'apprentissage, Champs de Markov, Feux de foret, Zones urbaines. Copyright : IEEE @INPROCEEDINGS{lafarge_icip05, author = {Lafarge, F. and Descombes, X. and Zerubia, J.}, title = {Textural Kernel for SVM Classification in Remote Sensing : Application to Forest Fire Detection and Urban Area Extraction}, year = {2005}, month = {septembre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Genoa, Italy}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/2005_lafarge_icip05.pdf}, keyword = {Support Vector Machines, Base d'apprentissage, Champs de Markov, Feux de foret, Zones urbaines} }

8 - Maximum A Posteriori Estimation of Radar Cross Section in SAR Images using the Heavy-Tailed Rayleigh Model. A. Achim et E.E. Kuruoglu et J. Zerubia. Dans Proc. European Signal Processing Conference (EUSIPCO), Antalya, Turkey, septembre 2005. @INPROCEEDINGS{achim_eusipco_05, author = {Achim, A. and Kuruoglu, E.E. and Zerubia, J.}, title = {Maximum A Posteriori Estimation of Radar Cross Section in SAR Images using the Heavy-Tailed Rayleigh Model}, year = {2005}, month = {septembre}, booktitle = {Proc. European Signal Processing Conference (EUSIPCO)}, address = {Antalya, Turkey}, pdf = {http://kilyos.ee.bilkent.edu.tr/~signal/defevent/papers/cr1741.pdf}, keyword = {} }

9 - Texture-adaptive mother wavelet selection for texture analysis. G.C.K. Abhayaratne et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Genoa, Italy, septembre 2005. Mots-clés : Texture, Paquet d'ondelettes, Adaptatif, Mere. @INPROCEEDINGS{abhayaratne_icip05, author = {Abhayaratne, G.C.K. and Jermyn, I. H. and Zerubia, J.}, title = {Texture-adaptive mother wavelet selection for texture analysis}, year = {2005}, month = {septembre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Genoa, Italy}, pdf = {http://www-sop.inria.fr/members/Ian.Jermyn/publications/Abhayaratne05icip.pdf}, keyword = {Texture, Paquet d'ondelettes, Adaptatif, Mere} } Abstract : Classification results obtained using wavelet-based texture analysis techniques vary with the choice of mother wavelet used in the methodology. We discuss the use of mother wavelet filters as parameters in a probabilistic approach to texture analysis based on adaptive biorthogonal wavelet packet bases. The optimal choice for the mother wavelet filters is estimated from the data, in addition to the other model parameters. The model is applied to the classification of single texture images and mosaics of Brodatz textures, the results showing improvement over the performance of standard wavelets for a given filter length.

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