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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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| author |
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{Jermyn, I. H. and Ishikawa, H.}, |
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{Globally optimal regions and boundaries as minimum ratio weight cycles}, |
| year |
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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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{http://dx.doi.org/10.1109/34.954599}, |
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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. |
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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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{Descombes, X. and Stoica, R. and Garcin, L. and Zerubia, J.}, |
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{Monte Carlo Methods and Applications}, |
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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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{Jalobeanu, A.}, |
| title |
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{Modèles, estimation bayésienne et algorithmes pour la déconvolution d'images satellitaires et aériennes}, |
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{2001}, |
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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.
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{Garcin, L. and Descombes, X. and Zerubia, J. and Le Men, H.}, |
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{Building extraction using a Markov point process}, |
| year |
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{2001}, |
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{October}, |
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{Proc. IEEE International Conference on Image Processing (ICIP)}, |
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{papier invité, Thessalonique, Grèce}, |
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{http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=958555}, |
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{} |
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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,
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{Jalobeanu, A. and Kingsbury, N. and Zerubia, J.}, |
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{Image deconvolution using Hidden Markov Tree modeling of complex wavelet packets}, |
| year |
= |
{2001}, |
| month |
= |
{October}, |
| booktitle |
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{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
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{Thessalonique, Grèce}, |
| url |
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{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=958988}, |
| keyword |
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{} |
| } |
|
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 |
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{Samson, C. and Blanc-Féraud, L. and Aubert, G. and Zerubia, J.}, |
| title |
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{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 |
= |
{} |
| } |
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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 |
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{2001}, |
| month |
= |
{September}, |
| booktitle |
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{Proc. GRETSI Symposium on Signal and Image Processing}, |
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{Toulouse, France}, |
| url |
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{http://documents.irevues.inist.fr/handle/2042/13236}, |
| keyword |
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{} |
| } |
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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 |
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{Rellier, G. and Descombes, X. and Zerubia, J. and Falzon, F.}, |
| title |
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{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 |
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{} |
| } |
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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 |
= |
{} |
| } |
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