Publications de Josiane Zerubia

Résultat de la recherche dans la liste des publications :

• 59 Articles
• 173 Articles de conférence
• 64 Rapports de recherche et Rapports techniques
• 7 Articles de collection ou Chapitres de livres
• 3 Livres

nouvelle recherche | bibtex

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173 Articles de conférence

102 - Texture analysis using adaptative biorthogonal wavelet packets. G.C.K. Abhayaratne et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Singapore, octobre 2004. Mots-clés : Adaptatif, Paquet d'ondelettes, Biorthogonal, Texture, Statistics. @INPROCEEDINGS{Abhayratne_icip04, author = {Abhayaratne, G.C.K. and Jermyn, I. H. and Zerubia, J.}, title = {Texture analysis using adaptative biorthogonal wavelet packets}, year = {2004}, month = {octobre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Singapore}, pdf = {http://www-sop.inria.fr/members/Ian.Jermyn/publications/Abhayaratne04icip.pdf}, keyword = {Adaptatif, Paquet d'ondelettes, Biorthogonal, Texture, Statistics} } Abstract : We discuss the use of adaptive biorthogonal wavelet packet bases in a probabilistic approach to texture analysis, thus combining the advantages of biorthogonal wavelets (FIR, linear phase) with those of a coherent texture model. The computation of the probability uses both the primal and dual coefcients of the adapted biorthogonal wavelet packet basis. The computation of the biorthogonal wavelet packet coefcients is done using a lifting scheme, which is very efficient. The model is applied to the classification of mosaics of Brodatz textures, the results showing improvement over the performance of the corresponding orthogonal wavelets.

103 - Unsupervised line network extraction from remotely sensed images by polyline process. C. Lacoste et X. Descombes et J. Zerubia et N. Baghdadi. Dans Proc. European Signal Processing Conference (EUSIPCO), University of Technology, Vienna, Austria, septembre 2004. @INPROCEEDINGS{lacoste04b, author = {Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, title = {Unsupervised line network extraction from remotely sensed images by polyline process}, year = {2004}, month = {septembre}, booktitle = {Proc. European Signal Processing Conference (EUSIPCO)}, address = {University of Technology, Vienna, Austria}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7079995}, pdf = {http://www.eurasip.org/Proceedings/Eusipco/Eusipco2004/defevent/papers/cr1608.pdf}, keyword = {} }

104 - A Discontinuity detector for building extraction from Digital Elevation Models by stochastic geometry. M. Ortner et X. Descombes et J. Zerubia. Dans Proc. European Signal Processing Conference (EUSIPCO), University of Technology, Vienna, Austria, septembre 2004. Note : this paper has received a Young Authors award @INPROCEEDINGS{ortner04b, author = {Ortner, M. and Descombes, X. and Zerubia, J.}, title = {A Discontinuity detector for building extraction from Digital Elevation Models by stochastic geometry}, year = {2004}, month = {septembre}, booktitle = {Proc. European Signal Processing Conference (EUSIPCO)}, address = {University of Technology, Vienna, Austria}, note = {this paper has received a Young Authors award}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7079720}, keyword = {} }

105 - SAR amplitude probability density function estimation based on a generalized Gaussian scattering model. G. Moser et J. Zerubia et S.B. Serpico. Dans Proc. SPIE Symposium on Remote Sensing, Maspalomas, Gran Canaria, Spain, septembre 2004. @INPROCEEDINGS{moser2004a, author = {Moser, G. and Zerubia, J. and Serpico, S.B.}, title = {SAR amplitude probability density function estimation based on a generalized Gaussian scattering model}, year = {2004}, month = {septembre}, booktitle = {Proc. SPIE Symposium on Remote Sensing}, address = {Maspalomas, Gran Canaria, Spain}, url = {http://dx.doi.org/10.1117/12.567853}, keyword = {} }

106 - Finite mixture models and stochastic EM for SAR amplitude probability density function estimation based on a dictionary of parametric families. G. Moser et J. Zerubia et S.B. Serpico. Dans Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Anchorage , USA, septembre 2004. @INPROCEEDINGS{moser2004b, author = {Moser, G. and Zerubia, J. and Serpico, S.B.}, title = {Finite mixture models and stochastic EM for SAR amplitude probability density function estimation based on a dictionary of parametric families}, year = {2004}, month = {septembre}, booktitle = {Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, address = {Anchorage , USA}, url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1368708}, keyword = {} }

107 - Tree Crown Extraction using Marked Point Processes. G. Perrin et X. Descombes et J. Zerubia. Dans Proc. European Signal Processing Conference (EUSIPCO), University of Technology, Vienna, Austria, septembre 2004. Mots-clés : RJMCMC, Processus ponctuels marques, Recuit Simule, Extraction de Houppiers, Extraction d'objets, Geometrie stochastique. @INPROCEEDINGS{perrin04a, author = {Perrin, G. and Descombes, X. and Zerubia, J.}, title = {Tree Crown Extraction using Marked Point Processes}, year = {2004}, month = {septembre}, booktitle = {Proc. European Signal Processing Conference (EUSIPCO)}, address = {University of Technology, Vienna, Austria}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/perrin_eusipco2004.pdf}, ps = {ftp://ftp-sop.inria.fr/ariana/Articles/perrin_eusipco2004.ps.gz}, keyword = {RJMCMC, Processus ponctuels marques, Recuit Simule, Extraction de Houppiers, Extraction d'objets, Geometrie stochastique} } Abstract : In this paper we aim at extracting tree crowns from remotely sensed images. Our approach is to consider that these images are some realizations of a marked point process. The first step is to define the geometrical objects that design the trees, and the density of the process. Then, we use a Reversible Jump Markov Chain Monte Carlo dynamics and a simulated annealing to get the maximum a posteriori estimator of the tree crown distribution on the image. Transitions of the Markov chain are managed by some specific proposition kernels. Results are shown on aerial images of poplars provided by IFN.

108 - A Reversible Jump MCMC sampler for building detection in image processing. M. Ortner et X. Descombes et J. Zerubia. Dans Monte Carlo Methods and Quasi-Monte Carlo Methods, series Special Se, Juan les Pins (France), juin 2004. @INPROCEEDINGS{mcmcqmc, author = {Ortner, M. and Descombes, X. and Zerubia, J.}, title = {A Reversible Jump MCMC sampler for building detection in image processing}, year = {2004}, month = {juin}, booktitle = {Monte Carlo Methods and Quasi-Monte Carlo Methods}, series = {Special Se}, address = {Juan les Pins (France)}, url = {http://link.springer.com/chapter/10.1007%2F3-540-31186-6_23}, keyword = {} }

109 - A Bayesian Geometric Model for Line Network Extraction from Satellite Images. C. Lacoste et X. Descombes et J. Zerubia et N. Baghdadi. Dans Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Montreal, Quebec, Canada, mai 2004. @INPROCEEDINGS{lacoste04a, author = {Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, title = {A Bayesian Geometric Model for Line Network Extraction from Satellite Images}, year = {2004}, month = {mai}, booktitle = {Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, address = {Montreal, Quebec, Canada}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1326607}, keyword = {} }

110 - Deconvolution in confocal microscopy with total variation regularization. N. Dey et L. Blanc-Féraud et C. Zimmer et Z. Kam et J.C. Olivo-Marin et J. Zerubia. Dans Proc. French-Danish Workshop on Spatial Statistics and Image Analysis in Biology (SSIAB), pages 117--120, mai 2004. @INPROCEEDINGS{Dey04b, author = {Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, title = {Deconvolution in confocal microscopy with total variation regularization}, year = {2004}, month = {mai}, booktitle = {Proc. French-Danish Workshop on Spatial Statistics and Image Analysis in Biology (SSIAB)}, pages = {117--120}, url = {http://www3.jouy.inra.fr/miaj/public/imaste/ssiab2004/program/abw92/}, keyword = {} }

111 - Texture analysis using probabilistic models of the unimodal and multimodal statistics of adaptative wavelet packet coefficients. R. Cossu et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Montreal, Canada, mai 2004. Mots-clés : Bimodale, Adaptatif, Paquet d'ondelettes, Texture, Mixture de gaussiennes, Statistics. @INPROCEEDINGS{cossu04a, author = {Cossu, R. and Jermyn, I. H. and Zerubia, J.}, title = {Texture analysis using probabilistic models of the unimodal and multimodal statistics of adaptative wavelet packet coefficients}, year = {2004}, month = {mai}, booktitle = {Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, address = {Montreal, Canada}, pdf = {http://www-sop.inria.fr/members/Ian.Jermyn/publications/Cossu04icassp.pdf}, keyword = {Bimodale, Adaptatif, Paquet d'ondelettes, Texture, Mixture de gaussiennes, Statistics} } Abstract : Although subband histograms of the wavelet coefficients of natural images possess a characteristic leptokurtotic form, this is no longer true for wavelet packet bases adapted to a given texture. Instead, three types of subband statistics are observed: Gaussian, leptokurtotic, and interestingly, in some subbands, multimodal histograms. These subbands are closely linked to the structure of the texture, and guarantee that the most probable image is not flat. Motivated by these observations, we propose a probabilistic model that takes them into account. Adaptive wavelet packet subbands are modelled as Gaussian, generalized Gaussian, or a constrained Gaussian mixture. We use a Bayesian methodology, finding MAP estimates for the adaptive basis, for subband model selection, and for subband model parameters. Results confirm the effectiveness of the proposed approach, and highlight the importance of multimodal subbands for texture discrimination and modelling.

112 - A deconvolution method for confocal microscopy with total variation regularization. N. Dey et L. Blanc-Féraud et C. Zimmer et Z. Kam et J.C. Olivo-Marin et J. Zerubia. Dans Proc. IEEE International Symposium on Biomedical Imaging (ISBI), Arlington, USA, avril 2004. Mots-clés : 3D confocal microscopy, Poisson deconvolution, total variation regularization. @INPROCEEDINGS{Dey04a, author = {Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, title = {A deconvolution method for confocal microscopy with total variation regularization}, year = {2004}, month = {avril}, booktitle = {Proc. IEEE International Symposium on Biomedical Imaging (ISBI)}, address = {Arlington, USA}, pdf = {http://dx.doi.org/10.1109/ISBI.2004.1398765}, keyword = {3D confocal microscopy, Poisson deconvolution, total variation regularization} } Abstract : Confocal laser scanning microscopy is a powerful and increasingly popular technique for 3D imaging of biological specimens. However the acquired images are degraded by blur from out-of-focus light and Poisson noise due to photon-limited detection. Several deconvolution methods have been proposed to reduce these degradations, including the Richardson-Lucy algorithm, which computes a maximum likelihood estimation adapted to Poisson statistics. However this method tends to amplify noise if used without regularizing constraint. Here, we propose to combine the Richardson-Lucy algorithm with a regularizing constraint based on total variation, whose smoothing avoids oscillations while preserving edges. We show on simulated images that this constraint improves the deconvolution result both visually and using quantitative measures.

113 - Marked Point Process in Image Analysis : from Context to Geometry. X. Descombes et F. Kruggel et C. Lacoste et M. Ortner et G. Perrin et J. Zerubia. Dans International Conference on Spatial Point Process Modelling and its Application (SPPA), Castellon, Spain, 2004. Mots-clés : RJMCMC, Extraction d'objets, Processus ponctuels marques, Geometrie stochastique. @INPROCEEDINGS{geostoch04a, author = {Descombes, X. and Kruggel, F. and Lacoste, C. and Ortner, M. and Perrin, G. and Zerubia, J.}, title = {Marked Point Process in Image Analysis : from Context to Geometry}, year = {2004}, booktitle = {International Conference on Spatial Point Process Modelling and its Application (SPPA)}, address = {Castellon, Spain}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/SPPA_2004.pdf}, ps = {ftp://ftp-sop.inria.fr/ariana/Articles/SPPA_2004.ps.gz}, keyword = {RJMCMC, Extraction d'objets, Processus ponctuels marques, Geometrie stochastique} } Abstract : We consider the marked point process framework as a natural extension of the Markov random field approach in image analysis. We consider a general model defined by its density allowing us to consider some geometrical constraints on objects and between objects in feature extraction problems. Some examples are derived for small brain lesions detection from MR Images, road network, tree crown and building extraction from remotely sensed images. The results obtained on real data show the relevance of the proposal approach.

114 - Extraction automatique de caricatures de bâtiments sur des Modèles Numériques d'Elèvation. M. Ortner et X. Descombes et J. Zerubia. Dans Pixels et Cités, ENSG, Marne la Vallée, France, novembre 2003. @INPROCEEDINGS{mathiaspix, author = {Ortner, M. and Descombes, X. and Zerubia, J.}, title = {Extraction automatique de caricatures de bâtiments sur des Modèles Numériques d'Elèvation}, year = {2003}, month = {novembre}, booktitle = {Pixels et Cités}, address = {ENSG, Marne la Vallée, France}, pdf = {Articles/PixelsCites2003.pdf}, keyword = {} }

115 - Un Nouveau Modèle Pour L'extraction de Caricatures de Bâtiments sur Des Modèles Numériques D'Élèvation. M. Ortner et X. Descombes et J. Zerubia. Dans Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA), Hammamet, Tunisia, octobre 2003. @INPROCEEDINGS{mathiastaima, author = {Ortner, M. and Descombes, X. and Zerubia, J.}, title = {Un Nouveau Modèle Pour L'extraction de Caricatures de Bâtiments sur Des Modèles Numériques D'Élèvation}, year = {2003}, month = {octobre}, booktitle = {Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA)}, address = {Hammamet, Tunisia}, url = {http://conferences.telecom-bretagne.eu/taima/_2003/}, keyword = {} }

116 - Wavelet-Based Superresolution in Astronomy. R. Willett et I. H. Jermyn et R. Nowak et J. Zerubia. Dans Proc. Astronomical Data Analysis Software and Systems, Strasbourg, France, octobre 2003. Mots-clés : Superresolution, Ondelettes, Astronomy. @INPROCEEDINGS{Willett03, author = {Willett, R. and Jermyn, I. H. and Nowak, R. and Zerubia, J.}, title = {Wavelet-Based Superresolution in Astronomy}, year = {2003}, month = {octobre}, booktitle = {Proc. Astronomical Data Analysis Software and Systems}, address = {Strasbourg, France}, pdf = {http://www-sop.inria.fr/members/Ian.Jermyn/publications/Willett03adass.pdf}, keyword = {Superresolution, Ondelettes, Astronomy} } Abstract : High-resolution astronomical images can be reconstructed from several blurred and noisy low-resolution images using a computational process known as superresolution reconstruction. Superresolution reconstruction is closely related to image deconvolution, except that the low-resolution images are not registered and their relative translations and rotations must be estimated in the process. The novelty of our approach to the superresolution problem is the use of wavelets and related multiresolution methods within an expectation-maximization reconstruction process to improve the accuracy and visual quality of the reconstructed image. Simulations demonstrate the effectiveness of the proposed method, including its ability to distinguish between tightly grouped stars with a small set of observations.

117 - Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery. M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision, at ICCV, Nice, France, octobre 2003. Mots-clés : Ordre superieur, Contour actif, Forme, Reseaux routiers, Segmentation, A priori. @INPROCEEDINGS{Rochery03a, author = {Rochery, M. and Jermyn, I. H. and Zerubia, J.}, title = {Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery}, year = {2003}, month = {octobre}, booktitle = {Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision}, address = {at ICCV, Nice, France}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/rochery_vlsm03.pdf}, keyword = {Ordre superieur, Contour actif, Forme, Reseaux routiers, Segmentation, A priori} } Abstract : We present a novel method for the incorporation of shape information into active contour models, and apply it to the extraction of line networks (e.g. road, water) from satellite imagery. The method is based on a new class of contour energies. These energies are quadratic on the space of one-chains in the image, as opposed to classical energies, which are linear. They can be expressed as double integrals on the contour, and thus incorporate non-trivial interactions between different contour points. The new energies describe families of contours that share complex geometric properties, without making reference to any particular shape. Networks fall into such a family, and to model them we make a particular choice of quadratic energy whose minima are reticulated. To optimize the energies, we use a level set approach. The forces derived from the new energies are non-local however, thus necessitating an extension of standard level set methods. Promising experimental results are obtained using real images.

118 - Texture Analysis: An Adaptive Probabilistic Approach. K. Brady et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Barcelona, Spain, septembre 2003. Mots-clés : Adaptatif, Paquet d'ondelettes, Statistics, Texture. @INPROCEEDINGS{Brady03, author = {Brady, K. and Jermyn, I. H. and Zerubia, J.}, title = {Texture Analysis: An Adaptive Probabilistic Approach}, year = {2003}, month = {septembre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Barcelona, Spain}, pdf = {http://www-sop.inria.fr/members/Ian.Jermyn/publications/Brady03icip.pdf}, keyword = {Adaptatif, Paquet d'ondelettes, Statistics, Texture} } Abstract : Two main issues arise when working in the area of texture segmentation: the need to describe the texture accurately by capturing its underlying structure, and the need to perform analyses on the boundaries of textures. Herein, we tackle these problems within a consistent probabilistic framework. Starting from a probability distribution on the space of infinite images, we generate a distribution on arbitrary finite regions by marginalization. For a Gaussian distribution, the computational requirement of diagonalization and the modelling requirement of adaptivity together lead naturally to adaptive wavelet packet models that capture the ‘significant amplitude features’ in the Fourier domain. Undecimated versions of the wavelet packet transform are used to diagonalize the Gaussian distribution efficiently, albeit approximately. We describe the implementation and application of this approach and present results obtained on several Brodatz texture mosaics.

119 - Extraction de réseaux linéiques à partir d'images satellitaires par processus Markov objet. C. Lacoste et X. Descombes et J. Zerubia et N. Baghdadi. Dans Proc. GRETSI Symposium on Signal and Image Processing, Paris, France, septembre 2003. @INPROCEEDINGS{lacosteXDJZNB03, author = {Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, title = {Extraction de réseaux linéiques à partir d'images satellitaires par processus Markov objet}, year = {2003}, month = {septembre}, booktitle = {Proc. GRETSI Symposium on Signal and Image Processing}, address = {Paris, France}, url = {http://documents.irevues.inist.fr/handle/2042/13529}, keyword = {} }

120 - Road Network Extraction in Remote Sensing by a Markov Object Process. C. Lacoste et X. Descombes et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Barcelona, Spain, septembre 2003. @INPROCEEDINGS{lacosteXDJZ03, author = {Lacoste, C. and Descombes, X. and Zerubia, J.}, title = {Road Network Extraction in Remote Sensing by a Markov Object Process}, year = {2003}, month = {septembre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Barcelona, Spain}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1247420}, keyword = {} }

121 - Étude D'une Nouvelle Classe de Contours Actifs Pour la Détection de Routes Dans Des Images de Télédétection. M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. GRETSI Symposium on Signal and Image Processing, Paris, France, septembre 2003. @INPROCEEDINGS{Rochery03, author = {Rochery, M. and Jermyn, I. H. and Zerubia, J.}, title = {Étude D'une Nouvelle Classe de Contours Actifs Pour la Détection de Routes Dans Des Images de Télédétection}, year = {2003}, month = {septembre}, booktitle = {Proc. GRETSI Symposium on Signal and Image Processing}, address = {Paris, France}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/rochery_gretsi03.pdf}, keyword = {} }

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