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Publications of 2001
Result of the query in the list of publications :
2 Articles |
1 - Globally optimal regions and boundaries as minimum ratio weight cycles.
I. H. Jermyn and H. Ishikawa. IEEE Trans. Pattern Analysis and Machine Intelligence, 23(10): pages 1075-1088, October 2001.
Keywords : Graph, Ratio, Cycle, Segmentation, Global minimum.
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.
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|
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{Jermyn, I. H. and Ishikawa, H.}, |
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{Globally optimal regions and boundaries as minimum ratio weight cycles}, |
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{2001}, |
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{October}, |
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{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
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{23}, |
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{1075-1088}, |
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{Graph, Ratio, Cycle, Segmentation, Global minimum} |
| } |
Abstract :
We describe a new form of energy functional for the modelling and identification of regions in images. The energy is defined on the space of boundaries in the image domain, and can incorporate very general combinations of modelling information both from the boundary (intensity gradients,ldots), em and from the interior of the region (texture, homogeneity,ldots). We describe two polynomial-time digraph algorithms for finding the em global minima of this energy. One of the algorithms is completely general, minimizing the functional for any choice of modelling information. It runs in a few seconds on a 256 times 256 image. The other algorithm applies to a subclass of functionals, but has the advantage of being extremely parallelizable. Neither algorithm requires initialization. |
|
2 - A RJMCMC algorithm for object processes in image processing.
X. Descombes and R. Stoica and L. Garcin and J. Zerubia. Monte Carlo Methods and Applications, 7(1-2): pages 149-156, 2001.
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{Monte Carlo Methods and Applications}, |
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{} |
| } |
|
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2 PhD Thesis and Habilitations |
1 - Modèles, estimation bayésienne et algorithmes pour la déconvolution d'images satellitaires et aériennes.
A. Jalobeanu. PhD Thesis, Universite de Nice Sophia Antipolis, December 2001.
@PHDTHESIS{aj01,
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2 - Processus ponctuels pour l'extraction de réseaux linéiques dans les images satellitaires et aériennes.
R. Stoica. PhD Thesis, Universite de Nice Sophia Antipolis, February 2001.
Keywords : Marked point process, Line networks, Road network, Stochastic geometry, RJMCMC.
@PHDTHESIS{rs01,
|
| author |
= |
{Stoica, R.}, |
| title |
= |
{Processus ponctuels pour l'extraction de réseaux linéiques dans les images satellitaires et aériennes}, |
| year |
= |
{2001}, |
| month |
= |
{February}, |
| school |
= |
{Universite de Nice Sophia Antipolis}, |
| pdf |
= |
{Theses/These-stoica.pdf}, |
| keyword |
= |
{Marked point process, Line networks, Road network, Stochastic geometry, RJMCMC} |
| } |
Résumé :
Les réseaux routiers, ou les réseaux hydrographiques, les vaisseaux sanguins ou bien les fissures dans les matériaux sont connus dans la communauté du traitement d'image sous le nom générique de réseaux liné¨iques. La théorie des processus ponctuels marqués est un cadre mathématique rigoureux qui donne la possibilité de modéliser l'image comme un ensemble d'objets en interaction. Les deux idées principales qui ont motivé ce travail sont : ces réseaux sont approchés par de segments de droite connectés, et les réseaux liné¨iques dans une image sont la réalisation d'un processus ponctuel de Gibbs. Le processus ponctuel qui modèlise les réseaux comporte deux composantes. Le premier terme ("Candy" modèle) gère les états et les interactions entre segments : densité, connectivité, alignement et répulsion des segments. L'emplacement du réseau dans l'image est trouvé grâce au second terme, le terme d'attache aux données. Cette composante du modèle est construite à partir de tests d'hypothèses. L'estimateur des réseaux dans l'image est donné par le minimum d'une fonction d'énergie de Gibbs. Pour trouver l'optimum global de cette fonction, nous mettons en {\oe}uvre un algorithme de type recuit simulé qui s'appuie, sur une dynamique de type Monte Carlo par Chaînes de Markov (MCMC) à sauts réversibles. Des résultats sont présentes sur des images aériennes, SPOT et RADAR (RSO). Nous abordons ensuite deux de problèmes ouverts liés au "Candy" modèle, mais d'un interêt théorique général : la convergence d'une dynamique de Monte Carlo à sauts reversibles, et l'estimation des paramètres des processus ponctuels. Une solution à ces problèmes pourrait ouvrir une nouvelle direction dans la recherche de méthodes non-supervisése en traitement d'image. |
Abstract :
Road or hydrographical networks, blood vessels or fissures in materials are all known by the image processing community under the general name of line networks. The theory of point processes is a rigourous mathematical framework which allows us to model an image as a set of interacting objects. The two main ideas which are the basis of this work are : these networks can be considered as connected segments, and the line networks in an image are the realization of a Gibbs point process. The point process used to model the networks has two components. The first one (Candy model) deals with the states and the interaction of the segments : density, connectivity, alignment, attraction and rejection. The location of the network is determined by the second component, the data term. This component is based on hypothesis tests. The network estimator is given by the minimum of a Gibbs energy. We build a simulated annealing algorithm in order to avoid local minima. This algorithm uses reversible jump Monte Carlo Markov Chain (RJMCMC) dynamics. Results are shown on aerial, SPOT and RADAR (SAR) images. Finally, we start a study on two open problems related to the Candy model, but of general theoretical interest : the convergence of a RJMCMC dynamics, and parameter estimation related to point processes. A solution to these problems would give a new direction for the research of unsupervised methods in image processing. |
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15 Conference articles |
1 - Building extraction using a Markov point process.
L. Garcin and X. Descombes and J. Zerubia and H. Le Men. In Proc. IEEE International Conference on Image Processing (ICIP), papier invité, Thessalonique, Grèce, October 2001.
@INPROCEEDINGS{xd01d,
|
| author |
= |
{Garcin, L. and Descombes, X. and Zerubia, J. and Le Men, H.}, |
| title |
= |
{Building extraction using a Markov point process}, |
| year |
= |
{2001}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{papier invité, Thessalonique, Grèce}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=958555}, |
| keyword |
= |
{} |
| } |
|
2 - Image deconvolution using Hidden Markov Tree modeling of complex wavelet packets.
A. Jalobeanu and N. Kingsbury and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Thessalonique, Grèce, October 2001.
@INPROCEEDINGS{aj01b,
|
| author |
= |
{Jalobeanu, A. and Kingsbury, N. and Zerubia, J.}, |
| title |
= |
{Image deconvolution using Hidden Markov Tree modeling of complex wavelet packets}, |
| year |
= |
{2001}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Thessalonique, Grèce}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=958988}, |
| keyword |
= |
{} |
| } |
|
3 - Two variational models for multispectral image classification.
C. Samson and L. Blanc-Féraud and G. Aubert and J. Zerubia. In Proc. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), Sophia Antipolis, France, September 2001.
@INPROCEEDINGS{lbf01a,
|
| author |
= |
{Samson, C. and Blanc-Féraud, L. and Aubert, G. and Zerubia, J.}, |
| title |
= |
{Two variational models for multispectral image classification}, |
| year |
= |
{2001}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, |
| address |
= |
{Sophia Antipolis, France}, |
| url |
= |
{http://link.springer.com/chapter/10.1007%2F3-540-44745-8_23}, |
| keyword |
= |
{} |
| } |
|
4 - Classification d'image satellitaire superspectrale en zone rurale et périurbaine.
O. Pony and U. Polverini and L. Gautret and J. Zerubia and X. Descombes. In Proc. GRETSI Symposium on Signal and Image Processing, Toulouse, France, September 2001.
@INPROCEEDINGS{xd01f,
|
| author |
= |
{Pony, O. and Polverini, U. and Gautret, L. and Zerubia, J. and Descombes, X.}, |
| title |
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{Classification d'image satellitaire superspectrale en zone rurale et périurbaine}, |
| year |
= |
{2001}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://documents.irevues.inist.fr/handle/2042/13236}, |
| keyword |
= |
{} |
| } |
|
5 - Un modèle markovien gaussien pour l'analyse de texture hyperspectrale en milieu urbain.
G. Rellier and X. Descombes and J. Zerubia and F. Falzon. In Proc. GRETSI Symposium on Signal and Image Processing, Toulouse, France, September 2001.
@INPROCEEDINGS{xd01g,
|
| author |
= |
{Rellier, G. and Descombes, X. and Zerubia, J. and Falzon, F.}, |
| title |
= |
{Un modèle markovien gaussien pour l'analyse de texture hyperspectrale en milieu urbain}, |
| year |
= |
{2001}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://documents.irevues.inist.fr/handle/2042/13293}, |
| keyword |
= |
{} |
| } |
|
6 - Recuit simulé pour le shape from shading.
X. Descombes and J.D. Durou and L. Petit. In Proc. GRETSI Symposium on Signal and Image Processing, Toulouse, France, September 2001.
@INPROCEEDINGS{xd01h,
|
| author |
= |
{Descombes, X. and Durou, J.D. and Petit, L.}, |
| title |
= |
{Recuit simulé pour le shape from shading}, |
| year |
= |
{2001}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://documents.irevues.inist.fr/handle/2042/13322}, |
| keyword |
= |
{} |
| } |
|
7 - Estimation de paramètres instrumentaux en imagerie satellitaire.
A. Jalobeanu and L. Blanc-Féraud and J. Zerubia. In Proc. GRETSI Symposium on Signal and Image Processing, Toulouse, France, September 2001.
@INPROCEEDINGS{aj01d,
|
| author |
= |
{Jalobeanu, A. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Estimation de paramètres instrumentaux en imagerie satellitaire}, |
| year |
= |
{2001}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://documents.irevues.inist.fr/handle/2042/13231}, |
| keyword |
= |
{} |
| } |
|
8 - Parameter estimation by a Markov Chain Monte Carlo technique for the Candy-model.
X. Descombes and M.N.M. van Lieshout and R. Stoica and J. Zerubia. In IEEE Workshop on Statistical Signal Processing, papier invité, Singapour, August 2001.
@INPROCEEDINGS{xd01e,
|
| author |
= |
{Descombes, X. and van Lieshout, M.N.M. and Stoica, R. and Zerubia, J.}, |
| title |
= |
{Parameter estimation by a Markov Chain Monte Carlo technique for the Candy-model}, |
| year |
= |
{2001}, |
| month |
= |
{August}, |
| booktitle |
= |
{IEEE Workshop on Statistical Signal Processing}, |
| address |
= |
{papier invité, Singapour}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=955212}, |
| keyword |
= |
{} |
| } |
|
9 - Region extraction from multiple images.
H. Ishikawa and I. H. Jermyn. In Proc. IEEE International Conference on Computer Vision (ICCV), Vancouver, Canada, July 2001.
Keywords : Stereo, Motion, global, optimum, Graph, Cycle.
@INPROCEEDINGS{IJ01a,
|
| author |
= |
{Ishikawa, H. and Jermyn, I. H.}, |
| title |
= |
{Region extraction from multiple images}, |
| year |
= |
{2001}, |
| month |
= |
{July}, |
| booktitle |
= |
{Proc. IEEE International Conference on Computer Vision (ICCV)}, |
| address |
= |
{Vancouver, Canada}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Jermyn01iccv.pdf}, |
| keyword |
= |
{Stereo, Motion, global, optimum, Graph, Cycle} |
| } |
Abstract :
We present a method for region identification in multiple
images. A set of regions in different images and the
correspondences on their boundaries can be thought of as
a boundary in the multi-dimensional space formed by the
product of the individual image domains. We minimize an
energy functional on the space of such boundaries, thereby
identifying simultaneously both the optimal regions in each
image and the optimal correspondences on their boundaries.
We use a ratio form for the energy functional, thus
enabling the global minimization of the energy functional
using a polynomial time graph algorithm, among other desirable
properties. We choose a simple form for this energy
that favours boundaries that lie on high intensity gradients
in each image, while encouraging correspondences between
boundaries in different images that match intensity values.
The latter tendency is weighted by a novel heuristic energy
that encourages the boundaries to lie on disparity or optical
flow discontinuities, although no dense optical flow or
disparity map is computed. |
|
10 - La poursuite de projection pour la classification d'images hyperspectrales texturées.
G. Rellier and X. Descombes and J. Zerubia and F. Falzon. In Proc. Journées des jeunes chercheurs en vision par ordinateur, Cahors, France, June 2001.
@INPROCEEDINGS{xd01i,
|
| author |
= |
{Rellier, G. and Descombes, X. and Zerubia, J. and Falzon, F.}, |
| title |
= |
{La poursuite de projection pour la classification d'images hyperspectrales texturées}, |
| year |
= |
{2001}, |
| month |
= |
{June}, |
| booktitle |
= |
{Proc. Journées des jeunes chercheurs en vision par ordinateur}, |
| address |
= |
{Cahors, France}, |
| url |
= |
{http://www.irit.fr/ORASIS2001/}, |
| ps |
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| keyword |
= |
{} |
| } |
|
11 - Apport de l'imagerie radar pour l'extraction des zones urbaines.
O. Viveros-Cancino and X. Descombes and J. Zerubia. In Proc. Journées des jeunes chercheurs en vision par ordinateur, Cahors, France, June 2001.
@INPROCEEDINGS{xd01j,
|
| author |
= |
{Viveros-Cancino, O. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Apport de l'imagerie radar pour l'extraction des zones urbaines}, |
| year |
= |
{2001}, |
| month |
= |
{June}, |
| booktitle |
= |
{Proc. Journées des jeunes chercheurs en vision par ordinateur}, |
| address |
= |
{Cahors, France}, |
| url |
= |
{http://www.irit.fr/ORASIS2001/}, |
| ps |
= |
{http://www.irit.fr/ORASIS2001/images/docs/viveros.ps.gz}, |
| keyword |
= |
{} |
| } |
|
12 - Estimation rapide du paramètre de régularisation en déconvolution d'images.
A. Jalobeanu and L. Blanc-Féraud and J. Zerubia. In Proc. Journées des jeunes chercheurs en vision par ordinateur, Cahors, France, June 2001.
@INPROCEEDINGS{aj01c,
|
| author |
= |
{Jalobeanu, A. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Estimation rapide du paramètre de régularisation en déconvolution d'images}, |
| year |
= |
{2001}, |
| month |
= |
{June}, |
| booktitle |
= |
{Proc. Journées des jeunes chercheurs en vision par ordinateur}, |
| address |
= |
{Cahors, France}, |
| url |
= |
{http://www.irit.fr/ORASIS2001/}, |
| ps |
= |
{http://www.irit.fr/ORASIS2001/images/docs/jalobeanu.ps.gz}, |
| keyword |
= |
{} |
| } |
|
13 - Judging whether multiple silhouettes can come from the same object.
D. Jacobs and P. Belhumeur and I. H. Jermyn. In Int. Workshop on Visual Form, Springer-Verlag Lecture Notes in Computer Science 2059, Capri, Italie, May 2001.
@INPROCEEDINGS{IJ01b,
|
| author |
= |
{Jacobs, D. and Belhumeur, P. and Jermyn, I. H.}, |
| title |
= |
{Judging whether multiple silhouettes can come from the same object}, |
| year |
= |
{2001}, |
| month |
= |
{May}, |
| booktitle |
= |
{Int. Workshop on Visual Form, Springer-Verlag Lecture Notes in Computer Science 2059}, |
| address |
= |
{Capri, Italie}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Jacobs01iwvf.pdf}, |
| keyword |
= |
{} |
| } |
Abstract :
We consider the problem of recognizing an object from its
silhouette. We focus on the case in which the camera translates, and
rotates about a known axis parallel to the image, such as when a mo-
bile robot explores an environment. In this case we present an algorithm
for determining whether a new silhouette could come from the same ob-
ject that produced two previously seen silhouettes. In a basic case, when
cross-sections of each silhouette are single line segments, we can check
for consistency between three silhouettes using linear programming. This
provides the basis for methods that handle more complex cases. We show
many experiments that demonstrate the performance of these methods
when there is noise, some deviation from the assumptions of the algo-
rithms, and partial occlusion. Previous work has addressed the problem
of precisely reconstructing an object using many silhouettes taken under
controlled conditions. Our work shows that recognition can be performed
without complete reconstruction, so that a small number of images can
be used, with viewpoints that are only partly constrained. |
|
14 - Modelling images with alpha-stable textures.
E.E. Kuruoglu and J. Zerubia. In Physics in Signal and Image Processing, Marseille, France, January 2001.
@INPROCEEDINGS{KuruJZ01,
|
| author |
= |
{Kuruoglu, E.E. and Zerubia, J.}, |
| title |
= |
{Modelling images with alpha-stable textures}, |
| year |
= |
{2001}, |
| month |
= |
{January}, |
| booktitle |
= |
{Physics in Signal and Image Processing}, |
| address |
= |
{Marseille, France}, |
| keyword |
= |
{} |
| } |
|
15 - Segmentation d'image haute résolution par processus Markov objet.
X. Descombes and S. Drot and M. Imberty and H. Le Men and J. Zerubia. In Séminaire Télédétection à très haute résolution spatiale et analyse d'image, Cemagref, Montpellier, France, 2001.
@INPROCEEDINGS{xd01k,
|
| author |
= |
{Descombes, X. and Drot, S. and Imberty, M. and Le Men, H. and Zerubia, J.}, |
| title |
= |
{Segmentation d'image haute résolution par processus Markov objet}, |
| year |
= |
{2001}, |
| booktitle |
= |
{Séminaire Télédétection à très haute résolution spatiale et analyse d'image, Cemagref}, |
| address |
= |
{Montpellier, France}, |
| url |
= |
{http://cemadoc.irstea.fr/oa/PUB00009549-segmentation-image-haute-resolution-par-processus.html}, |
| keyword |
= |
{} |
| } |
|
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4 Technical and Research Reports |
1 - Segmentation of textured satellite and aerial images by Bayesian inference and Markov Random Fields.
S. Wilson and J. Zerubia. Research Report 4336, INRIA, France, December 2001.
@TECHREPORT{wilsonJZ01,
|
| author |
= |
{Wilson, S. and Zerubia, J.}, |
| title |
= |
{Segmentation of textured satellite and aerial images by Bayesian inference and Markov Random Fields}, |
| year |
= |
{2001}, |
| month |
= |
{December}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{4336}, |
| address |
= |
{France}, |
| url |
= |
{https://hal.inria.fr/inria-00072251}, |
| pdf |
= |
{https://hal.inria.fr/file/index/docid/72251/filename/RR-4336.pdf}, |
| ps |
= |
{https://hal.inria.fr/docs/00/07/22/51/PS/RR-4336.ps}, |
| keyword |
= |
{} |
| } |
Résumé :
Nous étudions un modèle markovien double, initialement proposé par Melas et Wilson, pour la segmentation d'image. Le nombre de classes de l'image est obtenu par inférence bayésienne via un algorithme de Metropolis à saut réversible. Les mouvements habituellement utilisés dans une telle dynamique consistent en la fission ou la fusion de classes. Mais cela peut nécessiter beaucoup de temps de calcul, en particulier sur des images de grande taille. Ici, nous étudions des mouvements plus simples qui sont rapides à mettre en oeuvre, mais dont la mélangeance peut être longue. Nous proposons alors un schéma de fission/fusion plus complexe et comparons les performances obtenues. Nous effectuons des tests sur des images satellitai- res et aériennes. |
Abstract :
We investigate Bayesian solutions to image segmentation based on the double Markov random field model, originally proposed by Melas and Wilson. Inference on the number of classes in the image is done via reversible jump Metropolis moves. These moves, usually implemented by splitting and merging classes, can be very slow, making them impractical for large images. We investigate simpler reversible jump moves that are quick to implement but show that they may mix very slowly. We propose a more complex split and merge scheme and compare its performance. Tests are conducted on satellite and aerial images. |
|
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