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Publications of 2008
Result of the query in the list of publications :
5 Articles |
1 - Incorporating generic and specific prior knowledge in a multi-scale phase field model for road extraction from VHR images.
T. Peng and I. H. Jermyn and V. Prinet and J. Zerubia. IEEE Trans. Geoscience and Remote Sensing, 1(2): pages 139--146, June 2008.
Keywords : Dense urban areas, Geographic Information System (GIS), Multiscale, Road network, Variational methods, Very high resolution.
Copyright : ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
@ARTICLE{Peng08b,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{Incorporating generic and specific prior knowledge in a multi-scale phase field model for road extraction from VHR images}, |
| year |
= |
{2008}, |
| month |
= |
{June}, |
| journal |
= |
{IEEE Trans. Geoscience and Remote Sensing}, |
| volume |
= |
{1}, |
| number |
= |
{2}, |
| pages |
= |
{139--146}, |
| url |
= |
{http://dx.doi.org/10.1109/JSTARS.2008.922318}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/PengetalTGRS08.pdf}, |
| keyword |
= |
{Dense urban areas, Geographic Information System (GIS), Multiscale, Road network, Variational methods, Very high resolution} |
| } |
Abstract :
This paper addresses the problem of updating digital road maps in dense urban areas by extracting the main road network from very high resolution (VHR) satellite images. Building on the work of Rochery et al. (2005), we represent the road region as a 'phase field'. In order to overcome the difficulties due to the complexity of the information contained in VHR images, we propose a multi-scale statistical data model. It enables the integration of segmentation results from coarse resolution, which furnishes a simplified representation of the data, and fine resolution, which provides accurate details. Moreover, an outdated GIS digital map is introduced into the model, providing specific prior knowledge of the road network. This new term balances the effect of the generic prior knowledge describing the geometric shape of road networks (i.e. elongated and of low-curvature) carried by a 'phase field higher-order active contour' term. Promising results on QuickBird panchromatic images and comparisons with several other methods demonstrate the effectiveness of our approach. |
|
2 - Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling.
F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Journal of Photogrammetry and Remote Sensing, 63(3): pages 365-381, May 2008.
Keywords : Building extraction, 3D reconstruction, Digital Elevation Model, Stochastic geometry.
@ARTICLE{lafarge_jprs08,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
| title |
= |
{Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling}, |
| year |
= |
{2008}, |
| month |
= |
{May}, |
| journal |
= |
{Journal of Photogrammetry and Remote Sensing}, |
| volume |
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{63}, |
| number |
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{3}, |
| pages |
= |
{365-381}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_lafarge_jprs08.pdf}, |
| keyword |
= |
{Building extraction, 3D reconstruction, Digital Elevation Model, Stochastic geometry} |
| } |
Abstract :
In this paper, we present an automatic building extraction method from Digital Elevation Models based on an object approach.
First, a rough approximation of the building footprints is realized by a method based on marked point processes: the building
footprints are modeled by rectangle layouts. Then, these rectangular footprints are regularized by improving the connection
between the neighboring rectangles and detecting the roof height discontinuities. The obtained building footprints are structured
footprints: each element represents a specific part of an urban structure. Results are finally applied to a 3D-city modeling process. |
|
3 - Gap Filling of 3-D Microvascular Networs by Tensor Voting.
L. Risser and F. Plouraboue and X. Descombes. IEEE Trans. Medical Imaging, 27(5): pages 674-687, May 2008.
Copyright :
@ARTICLE{xavTMI3,
|
| author |
= |
{Risser, L. and Plouraboue, F. and Descombes, X.}, |
| title |
= |
{Gap Filling of 3-D Microvascular Networs by Tensor Voting}, |
| year |
= |
{2008}, |
| month |
= |
{May}, |
| journal |
= |
{IEEE Trans. Medical Imaging}, |
| volume |
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{27}, |
| number |
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{5}, |
| pages |
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{674-687}, |
| pdf |
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{http://ieeexplore.ieee.org/iel5/42/4497376/04389807.pdf?isnumber=4497376&prod=JNL&arnumber=4389807&arSt=674&ared=687&arAuthor=Risser%2C+L.%3B+Plouraboue%2C+F.%3B+Descombes%2C+X.}, |
| keyword |
= |
{} |
| } |
|
4 - A marked point process of rectangles and segments for automatic analysis of Digital Elevation Models..
M. Ortner and X. Descombes and J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 2008.
Keywords : Image procressing, Poisson point process, Stochastic geometry, Dense urban area, Digital Elevation Model, land register.
Copyright :
@ARTICLE{ortner08,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A marked point process of rectangles and segments for automatic analysis of Digital Elevation Models.}, |
| year |
= |
{2008}, |
| journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/27/88/82/PDF/ortner08.pdf}, |
| keyword |
= |
{Image procressing, Poisson point process, Stochastic geometry, Dense urban area, Digital Elevation Model, land register} |
| } |
|
5 - The Gibbs fields approach and related dynamics in image processing.
X. Descombes and E. Zhizhina. Condensed Matter Physics, 11(2(54)): pages 293-312, 2008.
Copyright : Institute for Condensed Matter
@ARTICLE{LNA08,
|
| author |
= |
{Descombes, X. and Zhizhina, E.}, |
| title |
= |
{The Gibbs fields approach and related dynamics in image processing}, |
| year |
= |
{2008}, |
| journal |
= |
{Condensed Matter Physics}, |
| volume |
= |
{11}, |
| number |
= |
{2(54)}, |
| pages |
= |
{293-312}, |
| keyword |
= |
{} |
| } |
|
 top of the page
4 PhD Thesis and Habilitations |
1 - New higher-order active contour models, shape priors, and multiscale analysis: their application to road network extraction from very high resolution satellite images.
T. Peng. PhD Thesis, Universite de Nice Sophia Antipolis, November 2008.
Keywords : Higher-order active contour, Phase Field, Prior, Multiresolution, Road network, Very high resolution.
Copyright :
@PHDTHESIS{Peng08d,
|
| author |
= |
{Peng, T.}, |
| title |
= |
{New higher-order active contour models, shape priors, and multiscale analysis: their application to road network extraction from very high resolution satellite images}, |
| year |
= |
{2008}, |
| month |
= |
{November}, |
| school |
= |
{Universite de Nice Sophia Antipolis}, |
| pdf |
= |
{http://tel.archives-ouvertes.fr/tel-00349768/fr/}, |
| keyword |
= |
{Higher-order active contour, Phase Field, Prior, Multiresolution, Road network, Very high resolution} |
| } |
Résumé :
L'objectif de cette thèse est de développer et de valider des approches robustes d'extraction semi-automatique de réseaux routiers en zone urbaine dense à partir d'images satellitaires optiques à très haute résolution (THR). Nos modèles sont fondés sur une modélisation par champs de phase des contours actifs d'ordre supérieur (CAOS). Le probléme est difficile pour deux raisons principales : les images THR sont intrinsèquement complexes, et certaines zones des réseaux peuvent prendre une topologie arbitraire. Pour remédier à la complexité de l'information contenue dans les images THR, nous proposons une modélisation statistique multi-résolution des données ainsi qu'un modèle multi-résolution contraint a priori. Ces derniers permettent l'intégration des résultats de segmentation de résolution brute et de résolution fine. De plus, dans le cadre particulier de la mise à jour de réseaux routiers, nous présentons un modèle de forme a priori spécifique, dérivé d'une ancienne carte numérique issue d'un SIG. Ce terme spécifique a priori équilibre l'effet de la connaissance a priori générique apportée par le modèle de CAOS, qui décrit la forme géométrique générale des réseaux routiers. Cependant, le modèle classique de CAOS souffre d'une limitation importante : la largeur des branches du réseau est contrainte à d'être similaire au maximum du rayon de courbure des branches du réseau, fournissant ainsi un modèle non satisfaisant dans le cas de réseaux aux branches droites et étroites ou aux branches fortement incurvées et larges. Nous résolvons ce problème en proposant deux nouveaux modèles : l'un contenant un terme additionnel, nonlocal, non-linéaire de CAOS, et l'autre contenant un terme additionnel, nonlocal, linéaire de CAOS. Ces deux termes permettent le contrôle séparé de la largeur et de la courbure des branches, et fournissent une meilleure prolongation pour une même largeur. Le terme linéaire a plusieurs avantages : d'une part il se calcule plus efficacement, d'autre part il peut modéliser plusieurs largeurs de branche simultanément. Afin de remédier à la difficulté du choix des paramètres de ces modèles, nous analysons les conditions de stabilité pour une longue barre d'une largeur donnée décrite par ces énergies, et montrons ainsi comment choisir rigoureusement les paramètres des fonctions d'énergie. Des expériences sur des images satellitaires THR et la comparaison avec d'autres modèles démontrent la supériorité de nos modèles. |
Abstract :
The objective of this thesis is to develop and validate robust approaches for the semi-automatic extraction of road networks in dense urban areas from very high resolution (VHR) optical satellite images. Our models are based on the recently developed higher-order active contour (HOAC) phase field framework. The problem is difficult for two main reasons: VHR images are intrinsically complex and network regions may have arbitrary topology. To tackle the complexity of the information contained in VHR images, we propose a multiresolution statistical data model and a multiresolution constrained prior model. They enable the integration of segmentation results from coarse resolution and fine resolution. Subsequently, for the particular case of road map updating, we present a specific shape prior model derived from an outdated GIS digital map. This specific prior term balances the effect of the generic prior knowledge carried by the HOAC model, which describes the geometric shape of road networks in general. However, the classical HOAC model suffers from a severe limitation: network branch width is constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. We solve this problem by introducing two new models: one with an additional nonlinear nonlocal HOAC term, and one with an additional linear nonlocal HOAC term. Both terms allow separate control of branch width and branch curvature, and furnish better prolongation for the same width, but the linear term has several advantages: it is more efficient from a computational standpoint, and it is able to model multiple widths simultaneously. To cope with the difficulty of parameter selection of these models, we analyze the stability conditions for a long bar with a given width described by these energies, and hence show how to choose rigorously the parameters of the energy functions. Experiments on VHR satellite images and comparisons with other approaches demonstrate the superiority of our models. |
|
2 - Algorithmes rapides d'optimisation convexe. Application à la reconstruction d'images et à la détection de changements.
P. Weiss. PhD Thesis, Universite de Nice Sophia Antipolis, November 2008.
Keywords : Convex optimization, nesterov scheme, Sparse representations, Total variation, Change detection, level lines.
Copyright :
@PHDTHESIS{These_Pweiss,
|
| author |
= |
{Weiss, P.}, |
| title |
= |
{Algorithmes rapides d'optimisation convexe. Application à la reconstruction d'images et à la détection de changements}, |
| year |
= |
{2008}, |
| month |
= |
{November}, |
| school |
= |
{Universite de Nice Sophia Antipolis}, |
| pdf |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/These_PWEISS_Compressee.pdf}, |
| keyword |
= |
{Convex optimization, nesterov scheme, Sparse representations, Total variation, Change detection, level lines} |
| } |
Résumé :
Cette thèse contient des contributions en analyse numérique et en vision par ordinateur. Dans une première partie, nous nous intéressons à la résolution rapide, par des méthodes de premier ordre, de problèmes d'optimisation convexe. Ces problèmes apparaissent naturellement dans de nombreuses tâches telles que la reconstruction d'images, l'échantillonnage compressif ou la décomposition d'images en texture et en géométrie. Ils ont la particularité d'être non différentiables ou très mal conditionnés. On montre qu'en utilisant des propriétés fines des fonctions à minimiser on peut obtenir des algorithmes de minimisation extrêmement efficaces. On analyse systématiquement leurs taux de convergence en utilisant des résultats récents dûs à Y. Nesterov. Les méthodes proposées correspondent - à notre connaissance - à l'état de l'art des méthodes de premier ordre. Dans une deuxième partie, nous nous intéressons au problème de la détection de changements entre deux images satellitaires prises au même endroit à des instants différents. Une des difficultés principales à surmonter pour résoudre ce problème est de s'affranchir des conditions d'illuminations différentes entre les deux prises de vue. Ceci nous mène à l'étude de l'invariance aux changements d'illuminations des lignes de niveau d'une image. On caractérise complètement les scènes qui fournissent des lignes de niveau invariantes. Celles-ci correspondent assez bien à des milieux urbains. On propose alors un algorithme simple de détection de changements qui fournit des résultats très satisfaisants sur des images synthétiques et des images Quickbird réelles. |
|
3 - Détection et classification de changements sur des scènes urbaines en télédétection.
A. Fournier. PhD Thesis, Institut Supérieur de l'Aéronautique et de l'Espace, October 2008.
Keywords : détection de changements, Satellite images, lignes de niveau, Classification, Urban areas, statistiques directionnelles.
@PHDTHESIS{Fournier08,
|
| author |
= |
{Fournier, A.}, |
| title |
= |
{Détection et classification de changements sur des scènes urbaines en télédétection}, |
| year |
= |
{2008}, |
| month |
= |
{October}, |
| school |
= |
{Institut Supérieur de l'Aéronautique et de l'Espace}, |
| url |
= |
{http://tel.archives-ouvertes.fr/tel-00463593/fr/}, |
| keyword |
= |
{détection de changements, Satellite images, lignes de niveau, Classification, Urban areas, statistiques directionnelles} |
| } |
Résumé :
Cette thèse aborde le problème de la détection de changements sur des images de scènes urbaines en télédétection. Les expériences ont été menées sur des couples d'images satellitaires panchromatiques haute résolution (< 1 m). À travers ce thème général, plusieurs problématiques, correspondant aux divers niveaux d'une chaîne de traitement, sont abordés, depuis la création d'un masque de changements jusqu'au raisonnement à un niveau objet. Dans ce manuscrit, nous abordons premièrement le problème de la détermination d'un masque de changements. Après avoir étudié les limites d'un algorithme de détection de changements, fondé sur l'analyse en composantes principales, nous proposons un algorithme tirant parti de l'invariance des lignes de niveau, fondé sur un modèle d'illumination et des hypothèses sur la régularité de la scène. Par la suite, nous abordons la classification des zones détectées comme changées au cours de l'étape précédente. D'abord, nous nous fondons uniquement sur les radiométries des couples de pixels. Enfin, nous étudions l'intérêt d'une composante géométrique dans la classification. Plus précisément, nous appliquons un algorithme d'approximation polygonale sur les zones connexes issues de la classification précédentes, puis nous classifions les formes obtenues compte tenu des orientations des côtés des polygones obtenus. |
Abstract :
This thesis addresses the problem of change detection on remotely sensed urban scenes. experiences were run on couples of high resolution (<1m) panchromatic satellite images. Through this general theme, different problems, corresponding to different levels of a processing chain were addressed, from the determination of a change mask to an object level reasoning. In this work, we first address the problem of determining a change mask. We study the assets and limits of a change detection algorithm based on a Principal Component Analysis. We then propose a new algorithm that relies on the invariance of the level lines. It is based on a simple illumination model and some hypotheses on the scene regularity. Then we address the classification of the zones detected as changed during our first step. This is done by only considering the radiometries of each pixel couple. Finally, we study the interest of a geometric component in our classification. More precisely, we apply a polygonal approximation algorithm on the connected zones generated by the first classification, then we classify the obtained shapes according to the orientations of the polygon edges. |
|
4 - Détection de zones brûlées après un feu de forêt à partir d'une seule image satellitaire SPOT 5 par techniques SVM.
O. Zammit. PhD Thesis, Universite de Nice Sophia Antipolis, September 2008.
Keywords : Classification, Satellite images, Burnt areas, Forest fires, Support Vector Machines, Region Growing.
Copyright :
@PHDTHESIS{zammit_these_08,
|
| author |
= |
{Zammit, O.}, |
| title |
= |
{Détection de zones brûlées après un feu de forêt à partir d'une seule image satellitaire SPOT 5 par techniques SVM}, |
| year |
= |
{2008}, |
| month |
= |
{September}, |
| school |
= |
{Universite de Nice Sophia Antipolis}, |
| url |
= |
{http://tel.archives-ouvertes.fr/tel-00345683/fr/}, |
| keyword |
= |
{Classification, Satellite images, Burnt areas, Forest fires, Support Vector Machines, Region Growing} |
| } |
Résumé :
Cette thèse aborde le problème de cartographie de zones brûlées à partir d'images satellitaires haute résolution. Nos modèles reposent sur le traitement d'une seule image SPOT 5, acquise après le feu afin de détecter automatiquement les zones brûlées.
Le modèle est fondé sur les Séparateurs à Vaste Marge (SVM), une technique de classification supervisée qui a démontré une meilleure précision et une meilleure capacité de généralisation que les algorithmes de classification plus traditionnels. Concernant notre problème de détection, les différentes zones brûlées possèdent des caractéristiques spectrales assez similaires, au contraire des zones non brûlées (végétation, routes, eau, zones urbaines, nuage, ombre...) dont les caractéristiques spectrales varient énormément. Nous proposons donc d'utiliser les One-Class SVM, une technique qui dérive des SVM mais qui n'utilise que des exemples de pixels brûlés pour les phases d'apprentissage et de classification.
Afin de prendre en compte l'information spatiale de l'image, l'algorithme OC-SVM est utilisé comme une technique de croissance de régions, ce qui permet de diminuer les fausses alarmes et d'améliorer les contours des zones brûlées.
De plus, la base d'exemple de pixels brûlés nécessaire à l'apprentissage des techniques SVM est déterminée automatiquement à partir de l'histogramme de l'image.
Finalement, la méthode de classification proposée est testée sur plusieurs images satellitaires afin de valider son efficacité selon le type de végétation et la surface des zones brûlées. Les zones brûlées obtenues sont comparées aux vérités de terrain fournies par le CNES, Infoterra France, le SERTIT, les Services Départementaux d'Incendies et de Secours ou l'Office National des Forêts. |
|
top of the page
20 Conference articles |
1 - Phase diagram of a long bar under a higher-order active contour energy: application to hydrographic network extraction from VHR satellite images.
A. El Ghoul and I. H. Jermyn and J. Zerubia. In International Conference on Pattern Recognition (ICPR), Tampa, Florida, December 2008.
Keywords : Phase diagram, Higher-order actif contours, Shape, river extraction.
@INPROCEEDINGS{ElGhoul08b,
|
| author |
= |
{El Ghoul, A. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Phase diagram of a long bar under a higher-order active contour energy: application to hydrographic network extraction from VHR satellite images}, |
| year |
= |
{2008}, |
| month |
= |
{December}, |
| booktitle |
= |
{International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Tampa, Florida}, |
| url |
= |
{https://hal.inria.fr/inria-00316619}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/31/66/19/PDF/icpr08aymenelghoul.pdf}, |
| keyword |
= |
{Phase diagram, Higher-order actif contours, Shape, river extraction} |
| } |
Abstract :
The segmentation of networks is important in several imaging domains, and models incorporating prior shape knowledge are often essential for the automatic performance of this task. Higher-order active contours
provide a way to include such knowledge, but their behaviour can vary significantly with parameter values: e.g. the same energy can model networks or a ‘gas of circles’. In this paper, we present a stability analysis
of a HOAC energy leading to the phase diagram of a long bar. The results, which are confirmed by numerical experiments, enable the selection of parameter values for the modelling of network shapes using the energy.
We apply the resulting model to the problem of hydrographic network extraction from VHR satellite images. |
|
2 - A Mixed Markov Model for Change Detection in Aerial Photos with Large Time Differences.
C. Benedek and T. Szirányi. In Proc. International Conference on Pattern Recognition (ICPR), Tampa, USA, December 2008.
Keywords : Aerial images, Change detection, mixed Markov models.
@INPROCEEDINGS{benedekICPR08,
|
| author |
= |
{Benedek, C. and Szirányi, T.}, |
| title |
= |
{A Mixed Markov Model for Change Detection in Aerial Photos with Large Time Differences}, |
| year |
= |
{2008}, |
| month |
= |
{December}, |
| booktitle |
= |
{Proc. International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Tampa, USA}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/35/91/16/PDF/benedekICPR08.pdf}, |
| keyword |
= |
{Aerial images, Change detection, mixed Markov models} |
| } |
Abstract :
In the paper we propose a novel multi-layer Mixed Markov model for detecting relevant changes in registered aerial images taken with significant time differences. The introduced approach combines global intensity statistics with local correlation and contrast features. A global energy optimization process simultaneously ensures optimal local feature selection and smooth, observation-consistent classification. Validation is given on real aerial photos. |
|
3 - A contrast equalization procedure for change detection algorithms: applications to remotely sensed images of urban areas.
A. Fournier and P. Weiss and L. Blanc-Féraud and G. Aubert. In International Conference on Pattern Recognition (ICPR), Tampa, USA, December 2008.
Keywords : Change detection, Level Lines, remote sensing.
Copyright : ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
@INPROCEEDINGS{l_lines_icpr08,
|
| author |
= |
{Fournier, A. and Weiss, P. and Blanc-Féraud, L. and Aubert, G.}, |
| title |
= |
{A contrast equalization procedure for change detection algorithms: applications to remotely sensed images of urban areas}, |
| year |
= |
{2008}, |
| month |
= |
{December}, |
| booktitle |
= |
{International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Tampa, USA}, |
| url |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/Conferences/icpr2008.pdf}, |
| pdf |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/Conferences/icpr2008.pdf}, |
| keyword |
= |
{Change detection, Level Lines, remote sensing} |
| } |
|
4 - Texture representation by geometric objects using a jump-diffusion process.
F. Lafarge and G. Gimel'farb. In Proc. British Machine Vision Conference (BMVC), Leeds, U.K., November 2008.
@INPROCEEDINGS{lafarge_bmvc08,
|
| author |
= |
{Lafarge, F. and Gimel'farb, G.}, |
| title |
= |
{Texture representation by geometric objects using a jump-diffusion process}, |
| year |
= |
{2008}, |
| month |
= |
{November}, |
| booktitle |
= |
{Proc. British Machine Vision Conference (BMVC)}, |
| address |
= |
{Leeds, U.K.}, |
| url |
= |
{http://www.comp.leeds.ac.uk/bmvc2008/proceedings/papers/86.pdf}, |
| keyword |
= |
{} |
| } |
|
5 - An extended phase field higher-order active contour model for networks and its application to road network extraction from VHR satellite images.
T. Peng and I. H. Jermyn and V. Prinet and J. Zerubia. In Proc. European Conference on Computer Vision (ECCV), Marseille, France, October 2008.
Keywords : Dense urban area, Phase Field, Road network, Variational methods, Very high resolution.
Copyright :
@INPROCEEDINGS{Peng08c,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{An extended phase field higher-order active contour model for networks and its application to road network extraction from VHR satellite images}, |
| year |
= |
{2008}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. European Conference on Computer Vision (ECCV)}, |
| address |
= |
{Marseille, France}, |
| pdf |
= |
{http://link.springer.com/chapter/10.1007%2F978-3-540-88690-7_38}, |
| keyword |
= |
{Dense urban area, Phase Field, Road network, Variational methods, Very high resolution} |
| } |
Abstract :
This paper addresses the segmentation from an image of entities that have the form of a 'network', i.e. the region in the image corresponding to the entity is composed of branches joining together at junctions, e.g. road or vascular networks. We present a new phase field higher-order active contour (HOAC) prior model for network regions, and apply it to the segmentation of road networks from very high resolution satellite images. This is a hard problem for two reasons. First, the images are complex, with much 'noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. Second, network regions are complex to model, because they may have arbitrary topology. In particular, we address a severe limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. To solve this problem, we propose a new HOAC prior energy term, and reformulate it as a nonlocal phase field energy. We analyse the stability of the new model, and find that in addition to solving the above problem by separating the interactions between points on the same and opposite sides of a network branch, the new model permits the modelling of two widths
simultaneously. The analysis also fixes some of the model parameters in terms of network width(s). After adding a likelihood energy, we use the model to extract the road network quasi-automatically from pieces of a QuickBird image, and compare the results to other models in the literature. The results demonstrate the superiority of the new model, the importance of strong prior knowledge in general, and of the new term in particular. |
|
6 - A Geometric Primitive Extraction Process for Remote Sensing Problems..
F. Lafarge and G. Gimel'farb and X. Descombes. In Proc. Advanced Concepts for Intelligent Vision Systems, pages 518-529, Juan-les-Pins, France, October 2008.
Copyright :
@INPROCEEDINGS{LGF2008,
|
| author |
= |
{Lafarge, F. and Gimel'farb, G. and Descombes, X.}, |
| title |
= |
{A Geometric Primitive Extraction Process for Remote Sensing Problems.}, |
| year |
= |
{2008}, |
| month |
= |
{October}, |
| booktitle |
= |
{ACIVS}, |
| pages |
= |
{518-529}, |
| address |
= |
{Juan-les-Pins, France}, |
| pdf |
= |
{http://www.springerlink.com/content/b228321527177226/}, |
| keyword |
= |
{} |
| } |
|
7 - Unsupervised One-Class SVM Using a Watershed Algorithm and Hysteresis Thresholding to Detect Burnt Areas.
O. Zammit and X. Descombes and J. Zerubia. In Proc. International Conference on Pattern Recognition and Image Analysis (PRIA), Nizhny Novgorod, Russia, September 2008.
Keywords : Classification, Segmentation, Support Vector Machines, Burnt areas, Forest fires, Satellite images.
Copyright :
@INPROCEEDINGS{zammit_pria_08,
|
| author |
= |
{Zammit, O. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Unsupervised One-Class SVM Using a Watershed Algorithm and Hysteresis Thresholding to Detect Burnt Areas}, |
| year |
= |
{2008}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. International Conference on Pattern Recognition and Image Analysis (PRIA)}, |
| address |
= |
{Nizhny Novgorod, Russia}, |
| pdf |
= |
{http://hal.inria.fr/inria-00316297/fr/}, |
| keyword |
= |
{Classification, Segmentation, Support Vector Machines, Burnt areas, Forest fires, Satellite images} |
| } |
|
8 - Combining One-Class Support Vector Machines and hysteresis thresholding: application to burnt area mapping.
O. Zammit and X. Descombes and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), Lausanne, Switzerland, August 2008.
Note : to appear.
Keywords : Classification, Satellite images, Support Vector Machines, Burnt areas, Forest fires, Clustering.
Copyright :
@INPROCEEDINGS{zammit_eusipco_08,
|
| author |
= |
{Zammit, O. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Combining One-Class Support Vector Machines and hysteresis thresholding: application to burnt area mapping}, |
| year |
= |
{2008}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Lausanne, Switzerland}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7080254}, |
| keyword |
= |
{Classification, Satellite images, Support Vector Machines, Burnt areas, Forest fires, Clustering} |
| } |
|
9 - Unsupervised Hierarchical Image Segmentation based on the TS-MRF model and Fast Mean-Shift Clustering.
R. Gaetano and G. Scarpa and G. Poggi and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), Lausanne, Switzerland, August 2008.
Keywords : Segmentation, Markov Random Fields, Mean Shift, Land Classification.
@INPROCEEDINGS{Gaetano2008,
|
| author |
= |
{Gaetano, R. and Scarpa, G. and Poggi, G. and Zerubia, J.}, |
| title |
= |
{Unsupervised Hierarchical Image Segmentation based on the TS-MRF model and Fast Mean-Shift Clustering}, |
| year |
= |
{2008}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Lausanne, Switzerland}, |
| pdf |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7080521}, |
| keyword |
= |
{Segmentation, Markov Random Fields, Mean Shift, Land Classification} |
| } |
Abstract :
Tree-Structured Markov Random Field (TS-MRF) models have been recently proposed to provide a hierarchical multiscale description of images. Based on such a model, the unsupervised image segmentation is carried out by means of a sequence of nested class splits, where each class is modeled as a local binary MRF.
We propose here a new TS-MRF unsupervised segmentation technique which improves upon the original algorithm by selecting a better tree structure and eliminating spurious classes. Such results are obtained by using the Mean-Shift procedure to estimate the number of pdf modes at each node (thus allowing for a non-binary tree), and to obtain a more reliable initial clustering for subsequent MRF optimization. To this end, we devise a new reliable and fast clustering algorithm based on the Mean-Shift technique. Experimental results prove the potential of the proposed method. |
|
10 - A new computationally efficient stochastic approach for building reconstruction from satellite data.
F. Lafarge and M. Durupt and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. In XXI ISPRS Congress, Part A, Beijing, China, July 2008.
Note : Copyright ISPRS
Keywords : 3D reconstruction, Building, satellite data, stochastic approach, jump process.
@INPROCEEDINGS{lafarge_isprs08,
|
| author |
= |
{Lafarge, F. and Durupt, M. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
| title |
= |
{A new computationally efficient stochastic approach for building reconstruction from satellite data}, |
| year |
= |
{2008}, |
| month |
= |
{July}, |
| booktitle |
= |
{XXI ISPRS Congress, Part A}, |
| address |
= |
{Beijing, China}, |
| note |
= |
{Copyright ISPRS}, |
| url |
= |
{http://www.isprs.org/proceedings/XXXVII/congress/3_pdf/40.pdf}, |
| keyword |
= |
{3D reconstruction, Building, satellite data, stochastic approach, jump process} |
| } |
|
11 - Indexing of mid-resolution satellite images with structural attributes.
A. Bhattacharya and M. Roux and H. Maitre and I. H. Jermyn and X. Descombes and J. Zerubia. In The International Society for Photogrammetry and Remote Sensing, Beijing, China, July 2008.
Keywords : Landscape, Segmentation, Features, Extraction, Classification, Modelling.
@INPROCEEDINGS{Bhattacharya08,
|
| author |
= |
{Bhattacharya, A. and Roux, M. and Maitre, H. and Jermyn, I. H. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Indexing of mid-resolution satellite images with structural attributes}, |
| year |
= |
{2008}, |
| month |
= |
{July}, |
| booktitle |
= |
{The International Society for Photogrammetry and Remote Sensing}, |
| address |
= |
{Beijing, China}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Bhattacharya08isprs.pdf}, |
| keyword |
= |
{Landscape, Segmentation, Features, Extraction, Classification, Modelling} |
| } |
Abstract :
Indexing and retrieval of satellite images 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. Entities in an image may be strongly correlated
with each other and can therefore be used to characterize geographical environments on the Earth’s surface.
The properties of road networks vary considerably from one geographical environment to another. The networks pertaining in a
satellite image can therefore be used to classify and retrieve such environments. In the work presented in this paper we have defined
7 such classes. These classes can be categorized as follows: 2 urban classes consisting of “Urban USA” and “Urban Europe”; 3
rural classes consisting of “Villages”, “Mountains” and “Fields”; an “Airports” class and a “Common” class (this can be considered
as a rejection class). These classes were then classified with the aid of geometrical and topological features computed from the road
networks occurring in them. In our work we have used two extraction methods simultaneously on an image to extract the road networks
pertaining in it. A set of 16 network features were computed from one extraction method and were categorized into 6 groups as follows:
6 measures of ‘density’, 4 measures of ‘curviness’, 2 measures of ‘homogeneity’, 1 measure of ‘length’, 2 measures of ‘distribution’
and 1 measure of ‘entropy’.
Due to certain limitations of these extraction methods there was a relative failure of network extraction in certain urban regions con-
taining narrow and dense road structures. This loss of information was circumvented by segmenting the urban regions and computing
a second set of geometrical and topological features from them. A set of 4 urban region features were computed and were categorized
into 3 groups as follows: 2 measures of ‘density’, 1 measure of ‘labels’ and 1 measure of ‘compactness’.
The 500 images (each of size 512x512 pixels) forming our database were selected from SPOT5 scenes with 5m resolution. From each
image a set of geometrical and topological features were computed from the road networks and urban regions. These features were
then used to classify the pre-defined geographical classes. Feature selection was done to avoid the burden of feature dimensionality
and increase the classification performance. A set of 20 features was selected from 36 features by Fisher Linear Discriminant (FLD)
analysis which gave the least classification error with an one-vs-rest linear Support Vector Machine (SVM).
The impact of spatial resolution and size of images on the feature set have been explored in this work. We took a closer look at the effect
of spatial resolution and size of images on the discriminative power of the feature set to classify the images belonging to the pre-defined
geographical classes. Tests were performed with feature selection by FLD and one-vs-rest linear SVM classification on a database with
images of 10m resolution. Another test was performed with feature selection by FLD and one-vs-rest linear SVM classification on a
database with 5m resolution images (each of size 256x256 pixels).
With the above mentioned approaches, we developed a novel method to classify large satellite images acquired by SPOT5 satellite (5m
resolution) with patches of images each of size 512x512 pixels extracted from them. There has been a large amount of work dedicated
to the classification of large satellite images at pixel level rather than considering image patches of different sizes. Classification of
image patches of different sizes from a large satellite image is a novel idea in the sense that the patches considered contain significant
coverage of a particular type of geographical environment.
Road networks and urban region features were computed from these image patches extracted from the large image. A one-vs-rest
Gaussian kernel SVM classification method was used to classify this large image. The classification results show that the image
patches were labeled with the class having the maximum geographical coverage of the area associated in the large image. The large
image was mapped into a “region matrix”, where each element of the matrix corresponds to a geographical class. This is a ‘hard’
classification and no inference can be drawn about the classification confidence.
In certain cases, this produces some anomalies, as a single patch may contain two or more different geographical coverages. In order
to have an estimate of these partial coverages, the output of the SVM was mapped into probabilities. These probability measures were
then studied to have a closer look at the classification accuracies. The results confirm that our method is able to classify a large image
into various geographical classes with a mean error of less than 10%.
Future studies can use operators to detect not only man-made structures like roads and urban areas, but also natural entities like rivers,
forests, etc. In this work we have restricted ourselves to a single resolution, but our methodology can be adapted to consider images
of higher resolutions from QuickBird and the future Pleiade satellite. At a better resolution it may be possible to extract different
structures like buildings, gardens, cross-roads, etc. This in turn will allow us to incorporate more classes to appropriately classify any
geographical environment. At an image resolution of 1m, we may imagine to have sub-classes of an existing class, e.g., classes like
urban Europe and urban USA can de divided into downtown, residential and industrial classes. |
|
12 - Extraction of main and secondary roads in VHR images using a higher-order phase field model.
T. Peng and I. H. Jermyn and V. Prinet and J. Zerubia. In Proc. XXI ISPRS Congress, Part A, pages 215-22, Beijing, China, July 2008.
Keywords : Road network, Urban areas, Satellite images, Segmentation, Modelling, Variational methods.
Copyright : ISPRS
@INPROCEEDINGS{Peng08a,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{Extraction of main and secondary roads in VHR images using a higher-order phase field model}, |
| year |
= |
{2008}, |
| month |
= |
{July}, |
| booktitle |
= |
{Proc. XXI ISPRS Congress, Part A}, |
| pages |
= |
{215-22}, |
| address |
= |
{Beijing, China}, |
| pdf |
= |
{http://www.isprs.org/proceedings/XXXVII/congress/3_pdf/33.pdf}, |
| keyword |
= |
{Road network, Urban areas, Satellite images, Segmentation, Modelling, Variational methods} |
| } |
Abstract :
This paper addresses the issue of extracting main and secondary road networks in dense urban areas from very high resolution (VHR, ~0.61m) satellite images. The difficulty with secondary roads lies in the low discriminative power of the grey-level distributions of road regions and the background, and the greater effect of occlusions and other noise on narrower roads. To tackle this problem, we use a previously developed higher-order active contour (HOAC) phase field model and augment it with an additional non-linear nonlocal term. The additional term allows separate control of road width and road curvature; thus more precise prior knowledge can be incorporated, and better road prolongation can be achieved for the same width. Promising results on QuickBird panchromatic images at reduced resolutions and comparisons with other models demonstrate the role and the efficiency of our new model. |
|
13 - Building reconstruction from a single DEM.
F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. In Proc. IEEE Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska, U.S., June 2008.
@INPROCEEDINGS{lafarge_cvpr08,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
| title |
= |
{Building reconstruction from a single DEM}, |
| year |
= |
{2008}, |
| month |
= |
{June}, |
| booktitle |
= |
{Proc. IEEE Computer Vision and Pattern Recognition (CVPR)}, |
| address |
= |
{Anchorage, Alaska, U.S.}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_lafarge_cvpr08.pdf}, |
| keyword |
= |
{} |
| } |
|
14 - Blind deconvolution for diffraction-limited fluorescence microscopy.
P. Pankajakshan and B. Zhang and L. Blanc-Féraud and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI), pages 740-743, Paris, France, May 2008.
Keywords : Confocal microscopy, Blind Deconvolution, point spread function, Richardson-Lucy algorithm, total variation regularization.
Copyright : This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
@INPROCEEDINGS{ppankajakshan08a,
|
| author |
= |
{Pankajakshan, P. and Zhang, B. and Blanc-Féraud, L. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Blind deconvolution for diffraction-limited fluorescence microscopy}, |
| year |
= |
{2008}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. IEEE International Symposium on Biomedical Imaging (ISBI)}, |
| pages |
= |
{740-743}, |
| address |
= |
{Paris, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_ppankajakshan08a.pdf}, |
| keyword |
= |
{Confocal microscopy, Blind Deconvolution, point spread function, Richardson-Lucy algorithm, total variation regularization} |
| } |
Abstract :
Optical Sections of biological samples obtained from a fluorescence Confocal Laser Scanning Microscopes (CLSM) are often degraded by out-of-focus blur and photon counting noise. Such physical constraints on the observation are a result of the diffraction-limited nature of the optical system, and the reduced amount of light detected by the photomultiplier respectively. Hence, the image stacks can benefit from postprocessing restoration methods based on deconvolution. The parameters of the acquisition system’s Point Spread Function (PSF) may vary during the course of experimentation, and so they have to be estimated directly from the observation data. We describe here an alternate minimization algorithm for the simultaneous blind estimation of the specimen 3D distribution of fluorescent sources and the PSF. Experimental results on real data show that the algorithm provides very good deconvolution results in comparison to theoretical microscope PSF models. |
|
15 - Automatic 3D modeling of urban scenes from satellite images.
F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. In Proc. SPACEAPPLI, Toulouse, France, April 2008.
@INPROCEEDINGS{lafarge_spaceappli08,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
| title |
= |
{Automatic 3D modeling of urban scenes from satellite images}, |
| year |
= |
{2008}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. SPACEAPPLI}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://www.toulousespaceshow.eu/tss08/spaceappli08/index.htm}, |
| keyword |
= |
{} |
| } |
|
16 - Compression artifacts reduction using variational methods: algorithms and experimental study.
P. Weiss and L. Blanc-Féraud and T. Andre and M. Antonini. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, USA, March 2008.
Keywords : compression artifact, fast l1 optimization, Total variation, contrast enhancement, nesterov scheme, jpeg2000.
Copyright :
@INPROCEEDINGS{ICASSP_WEISS,
|
| author |
= |
{Weiss, P. and Blanc-Féraud, L. and Andre, T. and Antonini, M.}, |
| title |
= |
{Compression artifacts reduction using variational methods: algorithms and experimental study}, |
| year |
= |
{2008}, |
| month |
= |
{March}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Las Vegas, USA}, |
| url |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/Conferences/icassp2008.pdf}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_ICASSP_WEISS.pdf}, |
| keyword |
= |
{compression artifact, fast l1 optimization, Total variation, contrast enhancement, nesterov scheme, jpeg2000} |
| } |
|
17 - AUTOMATIC FLAMINGO DETECTION USING A MULTIPLE BIRTH AND DEATH PROCESS.
S. Descamps and X. Descombes and A. Béchet and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, USA, March 2008.
Copyright : copyright IEEE 2008
@INPROCEEDINGS{descamps08,
|
| author |
= |
{Descamps, S. and Descombes, X. and Béchet, A. and Zerubia, J.}, |
| title |
= |
{AUTOMATIC FLAMINGO DETECTION USING A MULTIPLE BIRTH AND DEATH PROCESS}, |
| year |
= |
{2008}, |
| month |
= |
{March}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Las Vegas, USA}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_descamps08.pdf}, |
| keyword |
= |
{} |
| } |
|
18 - SATELLITE IMAGE RECONSTRUCTION FROM AN IRREGULAR SAMPLING.
E. Bughin and L. Blanc-Féraud and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, USA, March 2008.
Keywords : Irregular sampling, Variational methods, Fourier analysis, Satellite imaging.
Copyright :
@INPROCEEDINGS{Bughin08,
|
| author |
= |
{Bughin, E. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{SATELLITE IMAGE RECONSTRUCTION FROM AN IRREGULAR SAMPLING}, |
| year |
= |
{2008}, |
| month |
= |
{March}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Las Vegas, USA}, |
| url |
= |
{http://hal.inria.fr/docs/00/27/89/19/PDF/bughinICASSP08.pdf}, |
| keyword |
= |
{Irregular sampling, Variational methods, Fourier analysis, Satellite imaging} |
| } |
|
19 - Mixing Geometric and Radiometric Features for Change Classification.
A. Fournier and X. Descombes and J. Zerubia. In Proc. SPIE Symposium on Electronic Imaging, San Jose, USA, January 2008.
Keywords : Change detection, directional Statistics, polygonal approximation, Classification.
Copyright : Copyright 2008 SPIE and IS&T. This paper was published in the proceedings of IS&T/SPIE 20th Annual Symposium on Electronic Imaging and is made available as an electronic reprint (preprint) with permission of SPIE and IS&T. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
@INPROCEEDINGS{fournier_spie08,
|
| author |
= |
{Fournier, A. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Mixing Geometric and Radiometric Features for Change Classification}, |
| year |
= |
{2008}, |
| month |
= |
{January}, |
| booktitle |
= |
{Proc. SPIE Symposium on Electronic Imaging}, |
| address |
= |
{San Jose, USA}, |
| url |
= |
{http://hal.inria.fr/inria-00269853/fr/}, |
| keyword |
= |
{Change detection, directional Statistics, polygonal approximation, Classification} |
| } |
Abstract :
Most basic change detection algorithms use a pixel-based approach. Whereas such approach is quite well defined for monitoring important area changes (such as urban growth monitoring) in low resolution images, an object based approach seems more relevant when the change detection is specifically aimed toward targets (such as small buildings and vehicles). In this paper, we present an approach that mixes radiometric and geometric features to qualify the changed zones. The goal is to establish bounds (appearance, disappearance, substitution ...) between the detected changes and the underlying objects. We proceed by first clustering the change map (containing each pixel bitemporal radiosity) in different classes using the entropy-kmeans algorithm. Assuming that most man-made objects have a polygonal shape, a polygonal approximation algorithm is then used in order to characterize the resulting zone shapes. Hence allowing us to refine the primary rough classification, by integrating the polygon orientations in the state space. Tests are currently conducted on Quickbird data. |
|
20 - Diagramme de phase d'une énergie de type contours actifs d'ordre supérieur : le cas d'une barre longue.
A. El Ghoul and I. H. Jermyn and J. Zerubia. In 16ème congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA), Amiens, France, January 2008.
Keywords : Diagramme de phase, Contours actifs d'ordre supérieur, Shape, geometric prior, Télédétection.
@INPROCEEDINGS{ElGhoul08,
|
| author |
= |
{El Ghoul, A. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Diagramme de phase d'une énergie de type contours actifs d'ordre supérieur : le cas d'une barre longue}, |
| year |
= |
{2008}, |
| month |
= |
{January}, |
| booktitle |
= |
{16ème congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA)}, |
| address |
= |
{Amiens, France}, |
| url |
= |
{https://hal.inria.fr/inria-00319575}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/31/95/75/PDF/rfia08aymenelghoul.pdf}, |
| keyword |
= |
{Diagramme de phase, Contours actifs d'ordre supérieur, Shape, geometric prior, Télédétection} |
| } |
Résumé :
Dans cet article, nous présentons l’analyse de stabilité du modèle des “contours actifs d’ordre supérieur” (CAOS), pour l’extraction des réseaux routiers présents dans des images de télédétection. Le modèle énergétique des CAOS à minimiser présente des comportements différents en fonction des valeurs des paramètres du modèle.
Il s’est avéré que deux structures géométriques sont favorisées
par ce modèle : des structures linéiques et circulaires. Nous nous intéressons ici à la détermination du diagramme de phase, qui définit les gammes des valeurs des paramètres du modèle des CAOS, permettant d’obtenir des structures linéiques. |
Abstract :
In this paper, we present a stability analysis of a “higher-order active contour” (HOAC) model for road network extraction from remotely sensed images. The HOAC energy presents several different behaviours depending on the model parameter values. Two types of geometric structure are favoured, namely line networks and circles. In this
work, we derive the phase diagram giving the parameter ranges of the HOAC model that allow stable linear structures. |
|
top of the page
4 Technical and Research Reports |
1 - Modeling the statistics of high resolution SAR images.
V. Krylov and G. Moser and S.B. Serpico and J. Zerubia. Research Report 6722, INRIA, November 2008.
Keywords : Synthetic Aperture Radar (SAR) image, Probability density function, parametric estimation, finite mixture models, Stochastic EM (SEM).
Copyright : INRIA/ARIANA, 2008
@TECHREPORT{krylovDSEM08,
|
| author |
= |
{Krylov, V. and Moser, G. and Serpico, S.B. and Zerubia, J.}, |
| title |
= |
{Modeling the statistics of high resolution SAR images}, |
| year |
= |
{2008}, |
| month |
= |
{November}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{6722}, |
| url |
= |
{http://hal.archives-ouvertes.fr/inria-00342681/en/}, |
| pdf |
= |
{http://hal.archives-ouvertes.fr/docs/00/35/76/27/PDF/RR-6722.pdf}, |
| keyword |
= |
{Synthetic Aperture Radar (SAR) image, Probability density function, parametric estimation, finite mixture models, Stochastic EM (SEM)} |
| } |
Abstract :
In the context of remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of pixel intensities. In this work, we develop a parametric finite mixture model for modelling the statistics of intensities in high resolution Synthetic Aperture Radar (SAR) images. Along with the models we design an efficient parameter estimation scheme by integrating the Stochastic Expectation Maximization scheme and the Method of log-cumulants with an automatic technique to select, for each mixture component, an optimal parametric model taken from a predefined dictionary of parametric probability density functions (pdf). In particular, the proposed dictionary consists of eight most efficient state-of-the-art SAR-specific pdfs: Nakagami, log-normal, generalized Gaussian Rayleigh, Heavy-tailed Rayleigh, Weibull, K-root, Fisher and generalized Gamma. The experiment results with a set of several real SAR (COSMO-SkyMed) images demonstrate the high accuracy of the designed algorithm, both from the viewpoint of a visual comparison of the histograms, and from the viewpoint of quantitive measures such as correlation coefficient (always above 99,5%) . We stress, in particular, that the method proves to be effective on all the considered images, remaining accurate for multimodal and highly heterogeneous images. |
|
2 - Parametric blind deconvolution for confocal laser scanning microscopy-proof of concept.
P. Pankajakshan and L. Blanc-Féraud and B. Zhang and Z. Kam and J.C. Olivo-Marin and J. Zerubia. Research Report 6493, INRIA, April 2008.
Keywords : Confocal Laser Scanning Microscopy, Bayesian restoration, Blind Deconvolution, point spread function, Richardson-Lucy algorithm, Total variation.
Copyright : ARIANA/INRIA
@TECHREPORT{ppankajakshan08b,
|
| author |
= |
{Pankajakshan, P. and Blanc-Féraud, L. and Zhang, B. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Parametric blind deconvolution for confocal laser scanning microscopy-proof of concept}, |
| year |
= |
{2008}, |
| month |
= |
{April}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{6493}, |
| url |
= |
{https://hal.inria.fr/inria-00269265}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/27/02/92/PDF/report.pdf}, |
| keyword |
= |
{Confocal Laser Scanning Microscopy, Bayesian restoration, Blind Deconvolution, point spread function, Richardson-Lucy algorithm, Total variation} |
| } |
Résumé :
Nous proposons une méthode de restauration itérative d’images de fluorescence
CLSM et d’estimation paramétrique de la fonction de flou (PSF) du système d’acquisition.
Le CLSM est un microscope qui balaye un échantillon en 3D et utilise une sténopée pour
rejeter la lumière en dehors du point de focalisation. Néanmoins, la qualité des images
souffre de deux limitations physiques. La première est due à la diffraction due au système
optique et la seconde est due à la quantité réduite de lumière détectée par le tube
photo-multiplicateur (PMT). Ces limitations induisent respectivement un flou et du bruit
de comptage de photons. Les images peuvent alors bénéficier d’un post-traitement de
restauration fondé sur la déconvolution. Le problème à traiter est l’estimation simultanée
de la distribution 3D de l’échantillon des sources fluorescentes et de la PSF du microscope
(i.e. de déconvolution aveugle). En utilisant un modèle de processus physique
d’acquisition d’images microscopiques (CLSM), on réduit le nombre de paramètres libres
décrivant la PSF et on introduit des contraintes. On introduit aussi des connaissances a
priori sur l’échantillon ce qui permet de stabiliser le processus d’estimation et de favoriser
la convergence. Des expériences sur des données synthétiques montrent que la PSF peut
être estimée avec précision. Des expériences sur des données réelles montrent de bons
resultats de déconvolution en comparaison avec le modèle théorique de la PSF du microscope. |
Abstract :
We propose a method for the iterative restoration of fluorescence Confocal Laser Scanning Microscope (CLSM) images with parametric estimation of the acquisition system’s Point Spread Function (PSF). The CLSM is an optical fluorescence microscope that scans a specimen in 3D and uses a pinhole to reject most of the out-of-focus light. However, the quality of the image suffers from two primary physical limitations. The first is due to the diffraction-limited nature of the optical system and the second is due to the reduced amount of light detected by the photomultiplier tube (PMT). These limitations cause blur and photon counting noise respectively. The images can hence benefit from post-processing restoration methods based on deconvolution. An efficient method for parametric blind image deconvolution involves the simultaneous estimation of the specimen 3D distribution of fluorescent sources and the microscope PSF. By using a model for the microscope image acquisition physical process, we reduce the number of free parameters describing the PSF and introduce constraints. The parameters of the PSF may vary during the course of experimentation, and so they have to be estimated directly from the observation data. We also introduce a priori knowledge of the specimen that permits stabilization of the estimation process and favorizes the convergence. Experiments on simulated data show that the PSF could be estimatedwith a higher degree of accuracy and those done on real data show very good deconvolution results in comparison to the theoretical microscope PSF model. |
|
3 - On the illumination invariance of the level lines under directed light. Application to change detection.
P. Weiss and A. Fournier and L. Blanc-Féraud and G. Aubert. Research Report 6612, INRIA, 2008.
Keywords : Level Lines, illumination invariance, topographic map, Change detection, remote sensing, Urban areas.
Copyright :
@TECHREPORT{RR-6612,
|
| author |
= |
{Weiss, P. and Fournier, A. and Blanc-Féraud, L. and Aubert, G.}, |
| title |
= |
{On the illumination invariance of the level lines under directed light. Application to change detection}, |
| year |
= |
{2008}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{6612}, |
| url |
= |
{https://hal.archives-ouvertes.fr/inria-00310383}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/31/03/83/PDF/RR-6612.pdf}, |
| keyword |
= |
{Level Lines, illumination invariance, topographic map, Change detection, remote sensing, Urban areas} |
| } |
Abstract :
We analyze the illumination invariance of the level lines of an image. We show that if the scene surface has Lambertian reflectance and the light is directed, then a necessary condition for the level lines to be illumination invariant is that the 3D scene be developable and that its albedo satisfies some geometrical constraints. We then show that the level lines are ``almost'' invariant for piecewise developable surfaces. Such surfaces fit most of the urban structures. In a second part, this allows us to devise a very fast algorithm that detects changes between pairs of remotely sensed images of urban areas, independently of the lighting conditions. We show the effectiveness of the algorithm both on synthetic OpenGL scenes and real Quickbird images. We compare the efficiency of the proposed algorithm with other classical approaches and show that it is superior both in practice and in theory. |
|
4 - Reconstruction d'images satellitaires à partir d'un échantillonnage irrégulier.
M. Carlavan and P. Weiss and L. Blanc-Féraud and J. Zerubia. Research Report 6732, INRIA, 2008.
Keywords : l1 norm, nesterov scheme, total variation minimization, wavelet.
Copyright :
@TECHREPORT{RR-6732,
|
| author |
= |
{Carlavan, M. and Weiss, P. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Reconstruction d'images satellitaires à partir d'un échantillonnage irrégulier}, |
| year |
= |
{2008}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{6732}, |
| url |
= |
{http://hal.archives-ouvertes.fr/inria-00340975/fr/}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/34/09/75/PDF/RR-6732.pdf}, |
| keyword |
= |
{l1 norm, nesterov scheme, total variation minimization, wavelet} |
| } |
|
top of the page
2 Collection articles or Books chapters |
1 - Deconvolution of images.
J. Idier and L. Blanc-Féraud. In Bayesian approach to inverse problems, Ed. J. Idier, Publ. ISTE and John Wiley & Sons, 2008.
Keywords : Inverse Problems, Bayesian approach, Image procressing.
Copyright : ISTE Ltd
@INCOLLECTION{blancferaud08,
|
| author |
= |
{Idier, J. and Blanc-Féraud, L.}, |
| title |
= |
{Deconvolution of images}, |
| year |
= |
{2008}, |
| booktitle |
= |
{Bayesian approach to inverse problems}, |
| editor |
= |
{J. Idier}, |
| publisher |
= |
{ISTE and John Wiley & Sons}, |
| url |
= |
{http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1848210329.html}, |
| pdf |
= |
{http://onlinelibrary.wiley.com/doi/10.1002/9780470611197.ch6/summary}, |
| keyword |
= |
{Inverse Problems, Bayesian approach, Image procressing} |
| } |
|
2 - Unsupervised problems.
X. Descombes and Y. Goussard. In Bayesian approach to inverse problems, Ed. J. Idier, Publ. ISTE and John Wiley & Sons, 2008.
Note : to appear.
Keywords : Inverse Problems, Bayesian approach, Image procressing.
Copyright : ISTE Ltd
@INCOLLECTION{descombes08,
|
| author |
= |
{Descombes, X. and Goussard, Y.}, |
| title |
= |
{Unsupervised problems}, |
| year |
= |
{2008}, |
| booktitle |
= |
{Bayesian approach to inverse problems}, |
| editor |
= |
{J. Idier}, |
| publisher |
= |
{ISTE and John Wiley & Sons}, |
| url |
= |
{http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1848210329.html}, |
| pdf |
= |
{http://onlinelibrary.wiley.com/doi/10.1002/9780470611197.ch8/summary}, |
| keyword |
= |
{Inverse Problems, Bayesian approach, Image procressing} |
| } |
|
top of the page
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