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Les Publications
Résultat de la recherche dans la liste des publications :
90 Rapports de recherche et Rapports techniques |
14 - Reconstruction d'images satellitaires à partir d'un échantillonnage irrégulier. M. Carlavan et P. Weiss et L. Blanc-Féraud et J. Zerubia. Rapport de Recherche 6732, INRIA, 2008. Mots-clés : l1 norm, nesterov scheme, total variation minimization, wavelet. Copyright :
@TECHREPORT{RR-6732,
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author |
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{Carlavan, M. and Weiss, P. and Blanc-Féraud, L. and Zerubia, J.}, |
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{Reconstruction d'images satellitaires à partir d'un échantillonnage irrégulier}, |
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{2008}, |
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{INRIA}, |
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keyword |
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{l1 norm, nesterov scheme, total variation minimization, wavelet} |
} |
|
15 - Support Vector Machines for burnt area discrimination. O. Zammit et X. Descombes et J. Zerubia. Rapport de Recherche 6343, INRIA, novembre 2007. Mots-clés : Feux de foret, Zones brûlées, Imagerie satellitaire, Support Vector Machines, Classification.
@TECHREPORT{zammit_RR_07,
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{Zammit, O. and Descombes, X. and Zerubia, J.}, |
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{Support Vector Machines for burnt area discrimination}, |
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{2007}, |
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{http://hal.inria.fr/inria-00185101/fr/}, |
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keyword |
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{Feux de foret, Zones brûlées, Imagerie satellitaire, Support Vector Machines, Classification} |
} |
Résumé :
Ce rapport aborde le problème de l'évaluation des dégâts après un feux de forêt. La détection est effectuée à partir d'une seule image satellite (SPOT 5) acquise après le feu. Afin de détecter les zones brûlées, nous utilisons une approche récente de classification nommée SVM (Séparateurs à Vaste Marge). Cette méthode est comparée aux algorithmes de classification plus conventionnels comme les K-moyennes ou les K-plus proches voisins, qui sont régulièrement utilisés en traitement d'image. Nous proposons également une méthode de classification non supervisée combinant les K-moyennes et les SVM. Les résultats fournis par les différentes techniques sont comparés à des vérités de terrain sur diverses zones brûlées. |
Abstract :
This report addresses the problem of burnt area discrimination using remote sensing images. The detection is based on a single post-fire image acquired by SPOT 5 satellite. To delineate the burnt areas, we use a recent classification method called Support Vectors Machines (SVM). This approach is compared to more conventional classifiers such as K-means or K-nearest neighbours which are widely used in image processing. We also proposed a new automatic classification approach combining K-means and SVM. The results given by the different methods are finally compared to ground truths on various burnt areas |
|
16 - Détection de flamants roses par processus ponctuels marqués pour l'estimation de la taille des populations. S. Descamps et X. Descombes et A. Béchet et J. Zerubia. Research Report 6328, INRIA, octobre 2007. Mots-clés : Extraction d'objets, modélisation stochastique , Processus ponctuels marques, dynamique de naissance/mort, environnement, flamants roses.
@TECHREPORT{Descamps-Descombes,
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author |
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{Descamps, S. and Descombes, X. and Béchet, A. and Zerubia, J.}, |
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{Détection de flamants roses par processus ponctuels marqués pour l'estimation de la taille des populations}, |
year |
= |
{2007}, |
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{octobre}, |
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{INRIA}, |
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{Research Report}, |
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{6328}, |
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{http://hal.inria.fr/inria-00180811}, |
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{http://hal.inria.fr/docs/00/18/08/93/PDF/RR-Desc-Desc-Bech-Zeru.pdf}, |
keyword |
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{Extraction d'objets, modélisation stochastique , Processus ponctuels marques, dynamique de naissance/mort, environnement, flamants roses} |
} |
|
17 - An adaptive simulated annealing cooling schedule for object detection in images. M. Ortner et X. Descombes et J. Zerubia. Rapport de Recherche 6336, INRIA, octobre 2007. Mots-clés : Traitement d'image, Shape extraction, Spatial point process, Recuit Simule, Adaptive cooling schedule.
@TECHREPORT{Ortner-Descombes,
|
author |
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{Ortner, M. and Descombes, X. and Zerubia, J.}, |
title |
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{An adaptive simulated annealing cooling schedule for object detection in images}, |
year |
= |
{2007}, |
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{octobre}, |
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{INRIA}, |
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{Research Report}, |
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{6336}, |
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{https://hal.inria.fr/inria-00181764}, |
pdf |
= |
{https://hal.inria.fr/inria-00181764}, |
keyword |
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{Traitement d'image, Shape extraction, Spatial point process, Recuit Simule, Adaptive cooling schedule} |
} |
|
18 - Efficient schemes for total variation minimization under constraints in image processing. P. Weiss et L. Blanc-Féraud et G. Aubert. Rapport de Recherche 6260, INRIA, juillet 2007. Mots-clés : l1 norm, total variation minimization, duality lp norms, gradient and subgradient descent, nesterov scheme, texture + geometry decomposition.
@TECHREPORT{RR-6260,
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author |
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{Weiss, P. and Blanc-Féraud, L. and Aubert, G.}, |
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{Efficient schemes for total variation minimization under constraints in image processing}, |
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{2007}, |
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{l1 norm, total variation minimization, duality lp norms, gradient and subgradient descent, nesterov scheme, texture + geometry decomposition} |
} |
Résumé :
Ce papier présente de nouveaux algorithmes pour minimiser la variation totale, et plus généralement des normes l^1, sous des contraintes convexes. Ces algorithmes proviennent d'une avancée récente en optimisation convexe proposée par Yurii Nesterov. Suivant la régularité de l'attache aux données, nous résolvons soit un problème primal, soit un problème dual. Premièrement, nous montrons que les schémas standard de premier ordre permettent d'obtenir des solutions de précision epsilon en O(frac1epsilon^2) itérations au pire des cas. Pour une contrainte convexe quelconque, nous proposons un schéma qui permet d'obtenir une solution de précision epsilon en O(frac1epsilon) itérations. Pour une contrainte fortement convexe, nous résolvons un problème dual avec un schéma qui demande O(frac1sqrtepsilon) itérations pour obtenir une solution de précision epsilon. Suivant la contrainte, nous gagnons donc un à deux ordres dans la rapidité de convergence par rapport à des approches standard. Finalement, nous faisons quelques expériences numériques qui confirment les résultats théoriques sur de nombreux problèmes. |
Abstract :
This paper presents new algorithms to minimize total variation and more generally l^1-norms under a general convex constraint. The algorithms are based on a recent advance in convex optimization proposed by Yurii Nesterov citeNESTEROV. Depending on the regularity of the data fidelity term, we solve either a primal problem, either a dual problem. First we show that standard first order schemes allow to get solutions of precision epsilon in O(frac1epsilon^2) iterations at worst. For a general convex constraint, we propose a scheme that allows to obtain a solution of precision epsilon in O(frac1epsilon) iterations. For a strongly convex constraint, we solve a dual problem with a scheme that requires O(frac1sqrtepsilon) iterations to get a solution of precision epsilon. Thus, depending on the regularity of the data term, we gain from one to two orders of magnitude in the convergence rates with respect to standard schemes. Finally we perform some numerical experiments which confirm the theoretical results on various problems. |
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19 - A Three-layer MRF model for Object Motion Detection in Airborne Images. C. Benedek et T. Szirányi et Z. Kato et J. Zerubia. Rapport de Recherche 6208, INRIA, juin 2007. Mots-clés : Aerial images, Change detection, Camera motion, MRF.
@TECHREPORT{benedek_INRIARR07,
|
author |
= |
{Benedek, C. and Szirányi, T. and Kato, Z. and Zerubia, J.}, |
title |
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{A Three-layer MRF model for Object Motion Detection in Airborne Images}, |
year |
= |
{2007}, |
month |
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{juin}, |
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{INRIA}, |
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{Research Report}, |
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{6208}, |
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= |
{https://hal.inria.fr/inria-00150805}, |
pdf |
= |
{https://hal.inria.fr/inria-00150805}, |
keyword |
= |
{Aerial images, Change detection, Camera motion, MRF} |
} |
|
20 - Object extraction using a stochastic birth-and-death dynamics in continuum. X. Descombes et R. Minlos et E. Zhizhina. Rapport de Recherche 6135, INRIA, 2007. Mots-clés : birth and death process, Stochastic modeling, Ondelettes.
@TECHREPORT{RR-6135,
|
author |
= |
{Descombes, X. and Minlos, R. and Zhizhina, E.}, |
title |
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{Object extraction using a stochastic birth-and-death dynamics in continuum}, |
year |
= |
{2007}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{6135}, |
url |
= |
{https://hal.inria.fr/inria-00133726}, |
pdf |
= |
{http://hal.inria.fr/inria-00133726}, |
keyword |
= |
{birth and death process, Stochastic modeling, Ondelettes} |
} |
Abstract :
We define a new birth and death dynamics dealing with configurations of discs in the plane. We prove the convergence of the continuous process and propose a discrete scheme converging to the continuous case. This framework is developed to address image processing problems consisting in extracting objects. The derived algorithm is applied for tree crown extraction and bird detection from aerial images. The performance of this approach is shown on real data. |
|
21 - Hierarchical finite-state modeling for texture segmentation with application to forest classification. G. Scarpa et M. Haindl et J. Zerubia. Research Report 6066, INRIA, INRIA, France, décembre 2006. Mots-clés : Texture, Segmentation, Co-occurrence matrix, Approche structurelle, MCMC, Synthesis.
@TECHREPORT{scarparr06,
|
author |
= |
{Scarpa, G. and Haindl, M. and Zerubia, J.}, |
title |
= |
{Hierarchical finite-state modeling for texture segmentation with application to forest classification}, |
year |
= |
{2006}, |
month |
= |
{décembre}, |
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{INRIA}, |
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{Research Report}, |
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{6066}, |
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{INRIA, France}, |
url |
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{https://hal.inria.fr/inria-00118420}, |
keyword |
= |
{Texture, Segmentation, Co-occurrence matrix, Approche structurelle, MCMC, Synthesis} |
} |
Abstract :
In this research report we present a new model for texture representation which is particularly well suited for image analysis and segmentation. Any image is first discretized and then a hierarchical finite-state region-based model is automatically coupled with the data by means of a sequential optimization scheme, namely the Texture Fragmentation and Reconstruction (TFR) algorithm. The TFR algorithm allows to model both intra- and inter-texture interactions, and eventually addresses the segmentation task in a completely unsupervised manner. Moreover, it provides a hierarchical output, as the user may decide the scale at which the segmentation has to be given. Tests were carried out on both natural texture mosaics provided by the Prague Texture Segmentation Datagenerator Benchmark and remote-sensing data of forest areas provided by the French National Forest Inventory (IFN). |
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22 - A higher-order active contour model of a `gas of circles' and its application to tree crown extraction. P. Horvath et I. H. Jermyn et Z. Kato et J. Zerubia. Research Report 6026, INRIA, France, novembre 2006. Mots-clés : Extraction de Houppiers, Aerial images, Ordre superieur, Contour actif, Gaz de cercles, Forme.
@TECHREPORT{Horvath05,
|
author |
= |
{Horvath, P. and Jermyn, I. H. and Kato, Z. and Zerubia, J.}, |
title |
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{A higher-order active contour model of a `gas of circles' and its application to tree crown extraction}, |
year |
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{2006}, |
month |
= |
{novembre}, |
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{INRIA}, |
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{Research Report}, |
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{6026}, |
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{France}, |
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{http://hal.inria.fr/inria-00115631}, |
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= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2006_Horvath05.pdf}, |
keyword |
= |
{Extraction de Houppiers, Aerial images, Ordre superieur, Contour actif, Gaz de cercles, Forme} |
} |
Abstract :
Many image processing problems involve identifying the region in the image domain occupied by a given entity in the scene. Automatic solution of these problems requires models that incorporate significant prior knowledge about the shape of the region. Many methods for including such knowledge run into difficulties when the topology of the region is unknown a priori, for example when the entity is composed of an unknown number of similar objects. Higher-order active contours (HOACs) represent one method for the modelling of non-trivial prior knowledge about shape without necessarily constraining region topology, via the inclusion of non-local interactions between region boundary points in the energy defining the model. The case of an unknown number of circular objects arises in a number of domains, \eg medical, biological, nanotechnological, and remote sensing imagery. Regions composed of an a priori unknown number of circles may be referred to as a `gas of circles'. In this report, we present a HOAC model of a `gas of circles'. In order to guarantee stable circles, we conduct a stability analysis via a functional Taylor expansion of the HOAC energy around a circular shape. This analysis fixes one of the model parameters in terms of the others and constrains the rest. In conjunction with a suitable likelihood energy, we apply the model to the extraction of tree crowns from aerial imagery, and show that the new model outperforms other techniques. |
|
23 - A structural approach for 3D building reconstruction. F. Lafarge et X. Descombes et J. Zerubia et M. Pierrot-Deseilligny. Research Report 6048, INRIA, novembre 2006. Mots-clés : Reconstruction en 3D, Approche structurelle, Building, RJMCMC, Viterbi.
@TECHREPORT{Lafarge_rr_6048,
|
author |
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{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
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{A structural approach for 3D building reconstruction}, |
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= |
{2006}, |
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{novembre}, |
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{INRIA}, |
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{6048}, |
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{https://hal.inria.fr/inria-00114338}, |
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keyword |
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{Reconstruction en 3D, Approche structurelle, Building, RJMCMC, Viterbi} |
} |
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