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Publications of 2007
Result of the query in the list of publications :
6 Articles |
1 - Higher-Order Active Contour Energies for Gap Closure.
M. Rochery and I. H. Jermyn and J. Zerubia. Journal of Mathematical Imaging and Vision, 29(1): pages 1-20, September 2007.
Keywords : Gap closure, Higher-order, Active contour, Shape, Prior, Road network.
@ARTICLE{Rochery07,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher-Order Active Contour Energies for Gap Closure}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| journal |
= |
{Journal of Mathematical Imaging and Vision}, |
| volume |
= |
{29}, |
| number |
= |
{1}, |
| pages |
= |
{1-20}, |
| url |
= |
{http://dx.doi.org/10.1007/s10851-007-0021-x}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Rochery07.pdf}, |
| keyword |
= |
{Gap closure, Higher-order, Active contour, Shape, Prior, Road network} |
| } |
Abstract :
One of the main difficulties in extracting line networks from images, and in particular road networks from remote sensing images, is the existence of interruptions in the data caused, for example, by occlusions. These can lead to gaps in the extracted network that do not correspond to gaps in the real network. In this paper, we describe a higher-order active contour energy that in addition to favouring network-like regions, includes a prior term penalizing networks containing ‘nearby opposing extremities’, thereby making gaps in the extracted network less likely. The new energy term causes such extremities to attract one another during gradient descent. They thus move towards one another and join, closing the gap. To minimize the energy, we develop specific techniques to handle the high-order derivatives that appear in the gradient descent equation. We present the results of automatic extraction of networks from real remote-sensing images, showing the ability of the model to overcome interruptions. |
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2 - Gaussian approximations of fluorescence microscope point-spread function models.
B. Zhang and J. Zerubia and J.C. Olivo-Marin. Applied Optics, 46(10): pages 1819-1829, April 2007.
Copyright : © 2007 Optical Society of America
@ARTICLE{jz_applied_photo,
|
| author |
= |
{Zhang, B. and Zerubia, J. and Olivo-Marin, J.C.}, |
| title |
= |
{Gaussian approximations of fluorescence microscope point-spread function models}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| journal |
= |
{Applied Optics}, |
| volume |
= |
{46}, |
| number |
= |
{10}, |
| pages |
= |
{1819-1829}, |
| keyword |
= |
{} |
| } |
Abstract :
We comprehensively study the least-squares Gaussian approximations of the diffraction-limited 2D-3D paraxial-nonparaxial point-spread functions (PSFs) of the wide field fluorescence microscope (WFFM), the laser scanning confocal microscope (LSCM), and the disk scanning confocal microscope (DSCM). The PSFs are expressed using the Debye integral. Under an L∞ constraint imposing peak matching, optimal and near-optimal Gaussian parameters are derived for the PSFs. With an L1 constraint imposing energy conservation, an optimal Gaussian parameter is derived for the 2D paraxial WFFM PSF. We found that (1) the 2D approximations are all very accurate; (2) no accurate Gaussian approximation exists for 3D WFFM PSFs; and (3) with typical pinhole sizes, the 3D approximations are accurate for the DSCM and nearly perfect for the LSCM. All the Gaussian parameters derived in this study are in explicit analytical form, allowing their direct use in practical applications. |
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3 - Building Outline Extraction from Digital Elevation Models using Marked Point Processes.
M. Ortner and X. Descombes and J. Zerubia. International Journal of Computer Vision, 72(2): pages 107-132, April 2007.
Keywords : RJMCMC, Buildings, Stochastic geometry, Marked point process, Digital Elevation Model (DEM).
@ARTICLE{ortner_ijcv_05,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Building Outline Extraction from Digital Elevation Models using Marked Point Processes}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{72}, |
| number |
= |
{2}, |
| pages |
= |
{107-132}, |
| url |
= |
{http://www.springerlink.com/content/d563v16957427102/?p=873bd324c7c14049a45cc1f2905b5a86&pi=0}, |
| keyword |
= |
{RJMCMC, Buildings, Stochastic geometry, Marked point process, Digital Elevation Model (DEM)} |
| } |
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4 - ant colony optimization for image regularization based on a non-stationary Markov modeling.
S. Le Hegarat-Mascle and A. Kallel and X. Descombes. IEEE Trans. on Image Processing, 16(3): pages 865-878, March 2007.
Keywords : Markov Random Fields, Ants colonization.
@ARTICLE{Ants07,
|
| author |
= |
{Le Hegarat-Mascle, S. and Kallel, A. and Descombes, X.}, |
| title |
= |
{ant colony optimization for image regularization based on a non-stationary Markov modeling}, |
| year |
= |
{2007}, |
| month |
= |
{March}, |
| journal |
= |
{IEEE Trans. on Image Processing}, |
| volume |
= |
{16}, |
| number |
= |
{3}, |
| pages |
= |
{865-878}, |
| keyword |
= |
{Markov Random Fields, Ants colonization} |
| } |
Abstract :
Ant colony optimization (ACO) has been proposed as a promising tool for regularization in image classification. The algorithm is applied here in a different way than the classical transposition of the graph color affectation problem. The ants collect information through the image, from one pixel to the others. The choice of the path is a function of the pixel label, favoring paths within the same image segment. We show that this corresponds to an automatic adaptation of the neighborhood to the segment form, and that it outperforms the fixed-form neighborhood used in classical Markov random field regularization techniques. The performance of this new approach is illustrated on a simulated image and on actual remote sensing images |
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5 - Détection de feux de forêt par analyse statistique d'évènements rares à partir d'images infrarouges thermiques.
F. Lafarge and X. Descombes and J. Zerubia and S. Mathieu. Traitement du Signal, 24(1), 2007.
Note : copyright Traitement du Signal
Keywords : Gaussian Field, Rare event, DT-caracteristic, Intensity peak.
@ARTICLE{lafarge_ts06,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Mathieu, S.}, |
| title |
= |
{Détection de feux de forêt par analyse statistique d'évènements rares à partir d'images infrarouges thermiques}, |
| year |
= |
{2007}, |
| journal |
= |
{Traitement du Signal}, |
| volume |
= |
{24}, |
| number |
= |
{1}, |
| note |
= |
{copyright Traitement du Signal}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_lafarge_ts06.pdf}, |
| keyword |
= |
{Gaussian Field, Rare event, DT-caracteristic, Intensity peak} |
| } |
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6 - Computing Statistics from Man-Made Structures on the Earth's Surface for Indexing Satellite Images.
A. Bhattacharya and M. Roux and H. Maitre and I. H. Jermyn and X. Descombes and J. Zerubia. International Journal of Simulation Modelling, 6(2): pages 73--83, 2007.
@ARTICLE{Bhattacharya07,
|
| author |
= |
{Bhattacharya, A. and Roux, M. and Maitre, H. and Jermyn, I. H. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Computing Statistics from Man-Made Structures on the Earth's Surface for Indexing Satellite Images}, |
| year |
= |
{2007}, |
| journal |
= |
{International Journal of Simulation Modelling}, |
| volume |
= |
{6}, |
| number |
= |
{2}, |
| pages |
= |
{73--83}, |
| url |
= |
{http://www.ijsimm.com/Full_Papers/Fulltext2007/text6-2_73-83.pdf}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Bhattacharya07.pdf}, |
| keyword |
= |
{} |
| } |
Abstract :
Indexing and retrieval from remote sensing image databases relies on the extraction of appropriate information from the data about the entity of interest (e.g. land cover type) and on the robustness of this extraction to nuisance variables. Other entities in an image may be strongly correlated with the entity of interest and their properties can therefore be used to characterize this entity. The road network contained in an image is one example. The properties of road networks vary considerably from one geographical environment to another, and they can therefore be used to classify and retrieve such environments. In this paper, we define several such environments, and classify them with the aid of geometrical and topological features computed from the road networks occurring in them. The relative failure of network extraction methods in certain types of urban area obliges us to segment such areas and to add a second set of geometrical and topological features computed from the segmentations. To validate the approach, feature selection and SVM linear kernel classification are performed on the feature set arising from a diverse image database. |
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3 PhD Thesis and Habilitations |
1 - The 'Gas of circles' model and its application to tree crown extraction.
P. Horvath. PhD Thesis, Universite de Szeged, Universite de Nice Sophia Antipolis, December 2007.
Keywords : geometric prior, Contours actifs d'ordre supérieur, Phase Field, Gas of circles.
@PHDTHESIS{horvath_these,
|
| author |
= |
{Horvath, P.}, |
| title |
= |
{The 'Gas of circles' model and its application to tree crown extraction}, |
| year |
= |
{2007}, |
| month |
= |
{December}, |
| school |
= |
{Universite de Szeged, Universite de Nice Sophia Antipolis}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_horvath_these.pdf}, |
| keyword |
= |
{geometric prior, Contours actifs d'ordre supérieur, Phase Field, Gas of circles} |
| } |
|
2 - Modèles stochastiques pour la reconstruction tridimensionnelle d'environnements urbains.
F. Lafarge. PhD Thesis, Ecole des Mines de Paris, October 2007.
Keywords : 3D reconstruction, Urban areas, Satellite images, Structural approach, Simulated Annealing, MCMC.
@PHDTHESIS{lafarge_phd07,
|
| author |
= |
{Lafarge, F.}, |
| title |
= |
{Modèles stochastiques pour la reconstruction tridimensionnelle d'environnements urbains}, |
| year |
= |
{2007}, |
| month |
= |
{October}, |
| school |
= |
{Ecole des Mines de Paris}, |
| url |
= |
{http://tel.archives-ouvertes.fr/tel-00179695/en/}, |
| keyword |
= |
{3D reconstruction, Urban areas, Satellite images, Structural approach, Simulated Annealing, MCMC} |
| } |
Résumé :
Cette thèse aborde le problème de la reconstruction tridimensionnelle de zones urbaines à partir d'images satellitaires très haute résolution. Le contenu informatif de ce type de données est insuffisant pour permettre une utilisation efficace des nombreux algorithmes développés pour des données aériennes. Dans ce contexte, l'introduction de connaissances a priori fortes sur les zones urbaines est nécessaire. Les outils stochastiques sont particulièrement bien adaptés pour traiter cette problématique.
Nous proposons une approche structurelle pour aborder ce sujet. Cela consiste à modéliser un bâtiment comme un assemblage de modules urbains élémentaires extraits d'une bibliothèque de modèles 3D paramétriques. Dans un premier temps, nous extrayons les supports 2D de ces modules à partir d'un Modèle Numérique d' Elévation (MNE). Le résultat est un agencement de quadrilatères dont les éléments voisins sont connectés entre eux. Ensuite, nous reconstruisons les bâtiments en recherchant la configuration optimale de modèles 3D se fixant sur les supports précédemment extraits. Cette configuration correspond à la réalisation qui maximise une densité mesurant la cohérence entre la réalisation et le MNE, mais également prenant en compte des connaissances a priori telles que des lois d'assemblage des modules. Nous discutons enfin de la pertinence de cette approche en analysant les résultats obtenus à partir de données satellitaires (simulations PLEIADES). Des expérimentations sont également réalisées à partir d'images aériennes mieux résolues. |
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3 - Indexing of satellite images using structural information.
A. Bhattacharya. PhD Thesis, Ecole Nationale Supérieure des Télécommunications, 2007.
Keywords : Landscape, Segmentation, Features, Extraction, Classification, Data mining.
@PHDTHESIS{bhattacharya_these,
|
| author |
= |
{Bhattacharya, A.}, |
| title |
= |
{Indexing of satellite images using structural information}, |
| year |
= |
{2007}, |
| school |
= |
{Ecole Nationale Supérieure des Télécommunications}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_bhattacharya_these.pdf}, |
| keyword |
= |
{Landscape, Segmentation, Features, Extraction, Classification, Data mining} |
| } |
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28 Conference articles |
1 - Forest Fire Detection based on Gaussian field analysis.
F. Lafarge and X. Descombes and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), Poznan, Poland, September 2007.
Note : Copyright EURASIP
Keywords : Gaussian Field, DT-caracteristic, Forest fires.
@INPROCEEDINGS{lafarge_eusipco07,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Forest Fire Detection based on Gaussian field analysis}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Poznan, Poland}, |
| note |
= |
{Copyright EURASIP}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_lafarge_eusipco07.pdf}, |
| keyword |
= |
{Gaussian Field, DT-caracteristic, Forest fires} |
| } |
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