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|
Publications de type 'article'
Résultat de la recherche dans la liste des publications :
101 Articles |
51 - Detecting codimension-two objects in an image with Ginzburg-Landau models.
G. Aubert et J.F. Aujol et L. Blanc-Féraud. International Journal of Computer Vision, 65(1-2): pages 29-42, novembre 2005.
Mots-clés : Modele de Ginzburg-Landau, Detection de points, Segmentation, PDE, Images biologiques, Images SAR.
@ARTICLE{laure-ijcv05,
|
| author |
= |
{Aubert, G. and Aujol, J.F. and Blanc-Féraud, L.}, |
| title |
= |
{Detecting codimension-two objects in an image with Ginzburg-Landau models}, |
| year |
= |
{2005}, |
| month |
= |
{novembre}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{65}, |
| number |
= |
{1-2}, |
| pages |
= |
{29-42}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/GL_IJCV_5.pdf}, |
| keyword |
= |
{Modele de Ginzburg-Landau, Detection de points, Segmentation, PDE, Images biologiques, Images SAR} |
| } |
Abstract :
In this paper, we propose a new mathematical model for detecting in an image singularities of codimension greater than or equal to two. This means we want to detect points in a 2-D image or points and curves in a 3-D image. We drew one's inspiration from
Ginzburg-Landau (G-L) models which have proved their efficiency for modeling many phenomena in physics. We introduce the model, state its
mathematical properties and give some experimental results demonstrating its capability in image processing. |
|
52 - Point Processes for Unsupervised Line Network Extraction in Remote Sensing.
C. Lacoste et X. Descombes et J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 27(10): pages 1568-1579, octobre 2005.
@ARTICLE{lacoste05,
|
| author |
= |
{Lacoste, C. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Point Processes for Unsupervised Line Network Extraction in Remote Sensing}, |
| year |
= |
{2005}, |
| month |
= |
{octobre}, |
| journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
| volume |
= |
{27}, |
| number |
= |
{10}, |
| pages |
= |
{1568-1579}, |
| pdf |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=32189&arnumber=1498752&count=18&index=4}, |
| keyword |
= |
{} |
| } |
|
53 - Supervised Segmentation of Remote Sensing Images Based on a Tree-Structure MRF Model.
G. Poggi et G. Scarpa et J. Zerubia. IEEE Trans. Geoscience and Remote Sensing, 43(8): pages 1901-1911, août 2005.
Mots-clés : Classification, Segmentation, Champs de Markov.
@ARTICLE{ieeetgrs_05,
|
| author |
= |
{Poggi, G. and Scarpa, G. and Zerubia, J.}, |
| title |
= |
{Supervised Segmentation of Remote Sensing Images Based on a Tree-Structure MRF Model}, |
| year |
= |
{2005}, |
| month |
= |
{août}, |
| journal |
= |
{IEEE Trans. Geoscience and Remote Sensing}, |
| volume |
= |
{43}, |
| number |
= |
{8}, |
| pages |
= |
{1901-1911}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/36/32001/01487647.pdf?tp=&arnumber=1487647&isnumber=32001}, |
| keyword |
= |
{Classification, Segmentation, Champs de Markov} |
| } |
|
54 - Dual Norms and Image Decomposition Models.
J.F. Aujol et A. Chambolle. International Journal of Computer Vision, 63(1): pages 85-104, juin 2005.
Mots-clés : Decomposition d'images.
@ARTICLE{AujolChambolle,
|
| author |
= |
{Aujol, J.F. and Chambolle, A.}, |
| title |
= |
{Dual Norms and Image Decomposition Models}, |
| year |
= |
{2005}, |
| month |
= |
{juin}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{63}, |
| number |
= |
{1}, |
| pages |
= |
{85-104}, |
| pdf |
= |
{http://link.springer.com/article/10.1007/s11263-005-4948-3}, |
| keyword |
= |
{Decomposition d'images} |
| } |
|
55 - Invariant Bayesian estimation on manifolds.
I. H. Jermyn. Annals of Statistics, 33(2): pages 583--605, avril 2005.
Mots-clés : Estimation bayesienne, MAP, MMSE, Invariant, Metrique, Jeffrey's.
@ARTICLE{jermyn_annstat05,
|
| author |
= |
{Jermyn, I. H.}, |
| title |
= |
{Invariant Bayesian estimation on manifolds}, |
| year |
= |
{2005}, |
| month |
= |
{avril}, |
| journal |
= |
{Annals of Statistics}, |
| volume |
= |
{33}, |
| number |
= |
{2}, |
| pages |
= |
{583--605}, |
| url |
= |
{http://dx.doi.org/10.1214/009053604000001273}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/jermyn_annstat05.pdf}, |
| keyword |
= |
{Estimation bayesienne, MAP, MMSE, Invariant, Metrique, Jeffrey's} |
| } |
Abstract :
A frequent and well-founded criticism of the maximum em a posteriori (MAP) and minimum mean squared error (MMSE) estimates of a continuous parameter param taking values in a differentiable manifold paramspace is that they are not invariant to arbitrary `reparametrizations' of paramspace. This paper clarifies the issues surrounding this problem, by pointing out the difference between coordinate invariance, which is a em sine qua non for a mathematically well-defined problem, and diffeomorphism invariance, which is a substantial issue, and then provides a solution. We first show that the presence of a metric structure on paramspace can be used to define coordinate-invariant MAP and MMSE estimates, and we argue that this is the natural way to proceed. We then discuss the choice of a metric structure on paramspace. By imposing an invariance criterion natural within a Bayesian framework, we show that this choice is essentially unique. It does not necessarily correspond to a choice of coordinates. In cases of complete prior ignorance, when Jeffreys' prior is used, the invariant MAP estimate reduces to the maximum likelihood estimate. The invariant MAP estimate coincides with the minimum message length (MML) estimate, but no discretization or approximation is used in its derivation. |
|
56 - Modeling very Oscillating Signals. Application to Image Processing.
G. Aubert et J.F. Aujol. Applied Mathematics and Optimization, 51(2): pages 163--182, mars 2005.
@ARTICLE{AujolAubert,
|
| author |
= |
{Aubert, G. and Aujol, J.F.}, |
| title |
= |
{Modeling very Oscillating Signals. Application to Image Processing}, |
| year |
= |
{2005}, |
| month |
= |
{mars}, |
| journal |
= |
{Applied Mathematics and Optimization}, |
| volume |
= |
{51}, |
| number |
= |
{2}, |
| pages |
= |
{163--182}, |
| pdf |
= |
{http://link.springer.com/article/10.1007/s00245-004-0812-z}, |
| keyword |
= |
{} |
| } |
|
57 - Optimal Partitions, Regularized Solutions, and Application to Image Classification.
G. Aubert et J.F. Aujol. Applicable Analysis, 84(1): pages 15--35, janvier 2005.
@ARTICLE{AujolAubertclassif,
|
| author |
= |
{Aubert, G. and Aujol, J.F.}, |
| title |
= |
{Optimal Partitions, Regularized Solutions, and Application to Image Classification}, |
| year |
= |
{2005}, |
| month |
= |
{janvier}, |
| journal |
= |
{Applicable Analysis}, |
| volume |
= |
{84}, |
| number |
= |
{1}, |
| pages |
= |
{15--35}, |
| pdf |
= |
{http://www.math.u-bordeaux1.fr/~jaujol/HDR/A2.pdf}, |
| keyword |
= |
{} |
| } |
|
58 - Image Decomposition into a Bounded Variation Component and an Oscillating Component.
J.F. Aujol et G. Aubert et L. Blanc-Féraud et A. Chambolle. Journal of Mathematical Imaging and Vision, 22(1): pages 71--88, janvier 2005.
@ARTICLE{BLA05,
|
| author |
= |
{Aujol, J.F. and Aubert, G. and Blanc-Féraud, L. and Chambolle, A.}, |
| title |
= |
{Image Decomposition into a Bounded Variation Component and an Oscillating Component}, |
| year |
= |
{2005}, |
| month |
= |
{janvier}, |
| journal |
= |
{Journal of Mathematical Imaging and Vision}, |
| volume |
= |
{22}, |
| number |
= |
{1}, |
| pages |
= |
{71--88}, |
| pdf |
= |
{http://link.springer.com/article/10.1007/s10851-005-4783-8}, |
| keyword |
= |
{} |
| } |
|
59 - Modèle Paramétrique pour la Reconstruction Automatique en 3D de Zones Urbaines Denses à partir d'Images Satellitaires Haute Résolution.
F. Lafarge et X. Descombes et J. Zerubia et M. Pierrot-Deseilligny. Revue Française de Photogrammétrie et de Télédétection (SFPT), 180: pages 4--12, 2005.
Mots-clés : Reconstruction en 3D, Zones urbaines, Approche bayésienne, MCMC, Imagerie satellitaire.
Copyright : SFPT
@ARTICLE{lafarge_sfpt05,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
| title |
= |
{Modèle Paramétrique pour la Reconstruction Automatique en 3D de Zones Urbaines Denses à partir d'Images Satellitaires Haute Résolution}, |
| year |
= |
{2005}, |
| journal |
= |
{Revue Française de Photogrammétrie et de Télédétection (SFPT)}, |
| volume |
= |
{180}, |
| pages |
= |
{4--12}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2005_lafarge_sfpt05.pdf}, |
| keyword |
= |
{Reconstruction en 3D, Zones urbaines, Approche bayésienne, MCMC, Imagerie satellitaire} |
| } |
|
60 - Applications of Gibbs fields methods to image processing problems.
X. Descombes et E. Zhizhina. Problems of Information Transmission, 40(3): pages 108--125, septembre 2004.
Note : in Russian
@ARTICLE{DES04br,
|
| author |
= |
{Descombes, X. and Zhizhina, E.}, |
| title |
= |
{Applications of Gibbs fields methods to image processing problems}, |
| year |
= |
{2004}, |
| month |
= |
{septembre}, |
| journal |
= |
{Problems of Information Transmission}, |
| volume |
= |
{40}, |
| number |
= |
{3}, |
| pages |
= |
{108--125}, |
| note |
= |
{in Russian}, |
| pdf |
= |
{http://www.mathnet.ru/php/getFT.phtml?jrnid=ppi&paperid=146&what=fullt&option_lang=rus}, |
| keyword |
= |
{} |
| } |
|
61 - Applications of Gibbs fields methods to image processing problems.
X. Descombes et E. Zhizhina. Problems of Information Transmission, 40(3): pages 279-295, septembre 2004.
Note : in English
@ARTICLE{DES04be,
|
| author |
= |
{Descombes, X. and Zhizhina, E.}, |
| title |
= |
{Applications of Gibbs fields methods to image processing problems}, |
| year |
= |
{2004}, |
| month |
= |
{septembre}, |
| journal |
= |
{Problems of Information Transmission}, |
| volume |
= |
{40}, |
| number |
= |
{3}, |
| pages |
= |
{279-295}, |
| note |
= |
{in English}, |
| url |
= |
{http://link.springer.com/article/10.1023%2FB%3APRIT.0000044262.70555.5c}, |
| keyword |
= |
{} |
| } |
|
62 - Modelling SAR Images with a Generalization of the Rayleigh Distribution.
E.E. Kuruoglu et J. Zerubia. IEEE Trans. Image Processing, 13(4): pages 527 - 533, avril 2004.
@ARTICLE{Kuruoglu03,
|
| author |
= |
{Kuruoglu, E.E. and Zerubia, J.}, |
| title |
= |
{Modelling SAR Images with a Generalization of the Rayleigh Distribution}, |
| year |
= |
{2004}, |
| month |
= |
{avril}, |
| journal |
= |
{IEEE Trans. Image Processing}, |
| volume |
= |
{13}, |
| number |
= |
{4}, |
| pages |
= |
{527 - 533}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/83/28667/01284389.pdf?tp=&arnumber=1284389&isnumber=28667}, |
| keyword |
= |
{} |
| } |
|
63 - An object based approach for detecting smallbrain lesions: application to Virchow-Robin spaces.
X. Descombes et F. Kruggel et G. Wollny et H.J. Gertz. IEEE Trans. Medical Imaging, 23(2): pages 246--255, février 2004.
@ARTICLE{DES04a,
|
| author |
= |
{Descombes, X. and Kruggel, F. and Wollny, G. and Gertz, H.J.}, |
| title |
= |
{An object based approach for detecting smallbrain lesions: application to Virchow-Robin spaces}, |
| year |
= |
{2004}, |
| month |
= |
{février}, |
| journal |
= |
{IEEE Trans. Medical Imaging}, |
| volume |
= |
{23}, |
| number |
= |
{2}, |
| pages |
= |
{246--255}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/42/28264/01263613.pdf?tp=&arnumber=1263613&isnumber=28264}, |
| keyword |
= |
{} |
| } |
|
64 - A Gibbs point process for road extraction in remotely sensed images.
R. Stoica et X. Descombes et J. Zerubia. International Journal of Computer Vision, 57(2): pages 121--136, 2004.
@ARTICLE{STO04a,
|
| author |
= |
{Stoica, R. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A Gibbs point process for road extraction in remotely sensed images}, |
| year |
= |
{2004}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{57}, |
| number |
= |
{2}, |
| pages |
= |
{121--136}, |
| url |
= |
{http://www.springerlink.com/content/kr262t6084464n30/}, |
| keyword |
= |
{} |
| } |
|
65 - An adaptive Gaussian model for satellite image deblurring.
A. Jalobeanu et L. Blanc-Féraud et J. Zerubia. IEEE Trans. Image Processing, 13(4), 2004.
@ARTICLE{JAL04a,
|
| author |
= |
{Jalobeanu, A. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{An adaptive Gaussian model for satellite image deblurring}, |
| year |
= |
{2004}, |
| journal |
= |
{IEEE Trans. Image Processing}, |
| volume |
= |
{13}, |
| number |
= |
{4}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/83/28667/01284396.pdf?tp=&arnumber=1284396&isnumber=28667}, |
| keyword |
= |
{} |
| } |
|
66 - Texture Feature Analysis Using a Gauss-Markov Model in Hyperspectral Image Classification.
G. Rellier et X. Descombes et F. Falzon et J. Zerubia. IEEE Trans. Geoscience and Remote Sensing, 42(7): pages 1543--1551, 2004.
@ARTICLE{DES04c,
|
| author |
= |
{Rellier, G. and Descombes, X. and Falzon, F. and Zerubia, J.}, |
| title |
= |
{Texture Feature Analysis Using a Gauss-Markov Model in Hyperspectral Image Classification}, |
| year |
= |
{2004}, |
| journal |
= |
{IEEE Trans. Geoscience and Remote Sensing}, |
| volume |
= |
{42}, |
| number |
= |
{7}, |
| pages |
= |
{1543--1551}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/36/29162/01315838.pdf?tp=&arnumber=1315838&isnumber=29162}, |
| keyword |
= |
{} |
| } |
|
67 - Extraction automatique de caricatures de bâtiments a partir de modeles numeriques d'elevation par utilisation de processus ponctuels spatiaux.
M. Ortner et X. Descombes et J. Zerubia. Bulletin de la Société Française de Photogrammétrie et de Télédétection, 173-174: pages 83--92, 2004.
@ARTICLE{ORT04a,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Extraction automatique de caricatures de bâtiments a partir de modeles numeriques d'elevation par utilisation de processus ponctuels spatiaux}, |
| year |
= |
{2004}, |
| journal |
= |
{Bulletin de la Société Française de Photogrammétrie et de Télédétection}, |
| volume |
= |
{173-174}, |
| pages |
= |
{83--92}, |
| keyword |
= |
{} |
| } |
|
68 - Gamma-convergence of discrete functionals with nonconvex perturbation for image classification.
G. Aubert et L. Blanc-Féraud et R. March. SIAM Journal on Numerical Analysis, 42(3): pages 1128--1145, 2004.
@ARTICLE{BLA04,
|
| author |
= |
{Aubert, G. and Blanc-Féraud, L. and March, R.}, |
| title |
= |
{Gamma-convergence of discrete functionals with nonconvex perturbation for image classification}, |
| year |
= |
{2004}, |
| journal |
= |
{SIAM Journal on Numerical Analysis}, |
| volume |
= |
{42}, |
| number |
= |
{3}, |
| pages |
= |
{1128--1145}, |
| url |
= |
{http://epubs.siam.org/doi/abs/10.1137/S0036142902412336}, |
| keyword |
= |
{} |
| } |
|
69 - A nonlinear entropic variational model for image filtering.
A. Ben Hamza et H. Krim et J. Zerubia. EURASIP Journal on Applied Signal Processing, 16: pages 2408--2422, 2004.
@ARTICLE{JZHK04,
|
| author |
= |
{Ben Hamza, A. and Krim, H. and Zerubia, J.}, |
| title |
= |
{A nonlinear entropic variational model for image filtering}, |
| year |
= |
{2004}, |
| journal |
= |
{EURASIP Journal on Applied Signal Processing}, |
| volume |
= |
{16}, |
| pages |
= |
{2408--2422}, |
| url |
= |
{https://hal.inria.fr/hal-00784485/}, |
| keyword |
= |
{} |
| } |
|
70 - A Multiresolution Approach for Shape from Shading Coupling Deterministic and Stochastic Optimization.
A. Crouzil et X. Descombes et J.D. Durou. IEEE Trans. Pattern Analysis ans Machine Intelligence, 25(11): pages 1416--1421, novembre 2003.
Note : Special section on `Energy minimization methods in computer vision and pattern recognition'
@ARTICLE{crouzilXDJDD,
|
| author |
= |
{Crouzil, A. and Descombes, X. and Durou, J.D.}, |
| title |
= |
{A Multiresolution Approach for Shape from Shading Coupling Deterministic and Stochastic Optimization}, |
| year |
= |
{2003}, |
| month |
= |
{novembre}, |
| journal |
= |
{IEEE Trans. Pattern Analysis ans Machine Intelligence}, |
| volume |
= |
{25}, |
| number |
= |
{11}, |
| pages |
= |
{1416--1421}, |
| note |
= |
{Special section on `Energy minimization methods in computer vision and pattern recognition'}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/34/27807/01240116.pdf?tp=&arnumber=1240116&isnumber=27807}, |
| keyword |
= |
{} |
| } |
|
71 - Wavelet-based Level Set Evolution for Classification of Textured Images.
J.F. Aujol et G. Aubert et L. Blanc-Féraud. IEEE Trans. Image Processing, 12(12), 2003.
@ARTICLE{aujolGL,
|
| author |
= |
{Aujol, J.F. and Aubert, G. and Blanc-Féraud, L.}, |
| title |
= |
{Wavelet-based Level Set Evolution for Classification of Textured Images}, |
| year |
= |
{2003}, |
| journal |
= |
{IEEE Trans. Image Processing}, |
| volume |
= |
{12}, |
| number |
= |
{12}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/83/28122/01257399.pdf?tp=&arnumber=1257399&isnumber=28122}, |
| keyword |
= |
{} |
| } |
|
72 - Extraction automatique des réseaux linéiques à partir d'images satellitaires et aériennes par processus Markov objet.
C. Lacoste et X. Descombes et J. Zerubia et N. Baghdadi. Bulletin de la Société Française de Photogrammétrie et de Télédétection, 170: pages 13--22, 2003.
@ARTICLE{lacostesfpt,
|
| author |
= |
{Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, |
| title |
= |
{Extraction automatique des réseaux linéiques à partir d'images satellitaires et aériennes par processus Markov objet}, |
| year |
= |
{2003}, |
| journal |
= |
{Bulletin de la Société Française de Photogrammétrie et de Télédétection}, |
| volume |
= |
{170}, |
| pages |
= |
{13--22}, |
| url |
= |
{http://www.researchgate.net/profile/Nicolas_Baghdadi/publication/236882132_Extraction_automatique_des_rseaux_liniques__partir_dimages_satellitaires_et_ariennes_par_processus_Markov_objets/links/00463519e05ebd9e83000000.pdf?disableCoverPage=true}, |
| keyword |
= |
{} |
| } |
|
73 - Droplet Shapes for a Class of Models in Z^2 at Zero Temperature.
X. Descombes et E. Pechersky. Journal of Statistical Physics, 111(1-2): pages 129--169, 2003.
@ARTICLE{descombesEP,
|
| author |
= |
{Descombes, X. and Pechersky, E.}, |
| title |
= |
{Droplet Shapes for a Class of Models in Z^2 at Zero Temperature}, |
| year |
= |
{2003}, |
| journal |
= |
{Journal of Statistical Physics}, |
| volume |
= |
{111}, |
| number |
= |
{1-2}, |
| pages |
= |
{129--169}, |
| pdf |
= |
{http://link.springer.com/article/10.1023/A%3A1022252923753}, |
| keyword |
= |
{} |
| } |
|
74 - Classification de Textures Hyperspectrales Fondée sur un Modèle Markovien et Une Technique de Poursuite de Projection.
G. Rellier et X. Descombes et F. Falzon et J. Zerubia. Traitement du Signal, 20(1): pages 25--42, 2003.
@ARTICLE{rellierXDFFJZ,
|
| author |
= |
{Rellier, G. and Descombes, X. and Falzon, F. and Zerubia, J.}, |
| title |
= |
{Classification de Textures Hyperspectrales Fondée sur un Modèle Markovien et Une Technique de Poursuite de Projection}, |
| year |
= |
{2003}, |
| journal |
= |
{Traitement du Signal}, |
| volume |
= |
{20}, |
| number |
= |
{1}, |
| pages |
= |
{25--42}, |
| url |
= |
{http://documents.irevues.inist.fr/handle/2042/2216}, |
| keyword |
= |
{} |
| } |
|
75 - Satellite image deblurring using complex wavelet packets.
A. Jalobeanu et L. Blanc-Féraud et J. Zerubia. International Journal of Computer Vision, 51(3): pages 205--217, 2003.
@ARTICLE{JalobeaLBFJZ,
|
| author |
= |
{Jalobeanu, A. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Satellite image deblurring using complex wavelet packets}, |
| year |
= |
{2003}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{51}, |
| number |
= |
{3}, |
| pages |
= |
{205--217}, |
| pdf |
= |
{http://link.springer.com/article/10.1023/A%3A1021801918603}, |
| keyword |
= |
{} |
| } |
|
76 - Skewed alpha-stable distributions for modelling textures.
E.E. Kuruoglu et J. Zerubia. Pattern Recognition Letters, 24(1-3): pages 339--348, 2003.
@ARTICLE{Kuruoglu03a,
|
| author |
= |
{Kuruoglu, E.E. and Zerubia, J.}, |
| title |
= |
{Skewed alpha-stable distributions for modelling textures}, |
| year |
= |
{2003}, |
| journal |
= |
{Pattern Recognition Letters}, |
| volume |
= |
{24}, |
| number |
= |
{1-3}, |
| pages |
= |
{339--348}, |
| url |
= |
{http://www.sciencedirect.com/science/article/pii/S0167865502002477}, |
| keyword |
= |
{} |
| } |
|
77 - Marked Point Processes in Image Analysis.
X. Descombes et J. Zerubia. IEEE Signal Processing Magazine, 19(5): pages 77-84, septembre 2002.
@ARTICLE{XDJZ,
|
| author |
= |
{Descombes, X. and Zerubia, J.}, |
| title |
= |
{Marked Point Processes in Image Analysis}, |
| year |
= |
{2002}, |
| month |
= |
{septembre}, |
| journal |
= |
{IEEE Signal Processing Magazine}, |
| volume |
= |
{19}, |
| number |
= |
{5}, |
| pages |
= |
{77-84}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/79/22084/01028354.pdf?tp=&arnumber=1028354&isnumber=22084}, |
| keyword |
= |
{} |
| } |
|
78 - Extension of phase correlation to subpixel registration.
H. Foroosh et J. Zerubia et M. Berthod. IEEE Trans. on Image Processing, 11(3): pages 188 - 200, mars 2002.
@ARTICLE{forooshjzmb,
|
| author |
= |
{Foroosh, H. and Zerubia, J. and Berthod, M.}, |
| title |
= |
{Extension of phase correlation to subpixel registration}, |
| year |
= |
{2002}, |
| month |
= |
{mars}, |
| journal |
= |
{IEEE Trans. on Image Processing}, |
| volume |
= |
{11}, |
| number |
= |
{3}, |
| pages |
= |
{188 - 200}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/83/21305/00988953.pdf?tp=&arnumber=988953&isnumber=21305}, |
| keyword |
= |
{} |
| } |
|
79 - Local registration and deformation of a road cartographic database on a SPOT Satellite Image.
G. Rellier et X. Descombes et J. Zerubia. Pattern Recognition, 35(10), 2002.
@ARTICLE{rellierXDJZ,
|
| author |
= |
{Rellier, G. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Local registration and deformation of a road cartographic database on a SPOT Satellite Image}, |
| year |
= |
{2002}, |
| journal |
= |
{Pattern Recognition}, |
| volume |
= |
{35}, |
| number |
= |
{10}, |
| url |
= |
{http://www.sciencedirect.com/science/article/pii/S0031320301001807}, |
| keyword |
= |
{} |
| } |
|
80 - Hyperparameter estimation for satellite image restoration using a MCMC Maximum Likelihood method.
A. Jalobeanu et L. Blanc-Féraud et J. Zerubia. Pattern Recognition, 35(2): pages 341--352, 2002.
@ARTICLE{jalo02h,
|
| author |
= |
{Jalobeanu, A. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Hyperparameter estimation for satellite image restoration using a MCMC Maximum Likelihood method}, |
| year |
= |
{2002}, |
| journal |
= |
{Pattern Recognition}, |
| volume |
= |
{35}, |
| number |
= |
{2}, |
| pages |
= |
{341--352}, |
| url |
= |
{http://www.sciencedirect.com/science/article/pii/S0031320300001783}, |
| keyword |
= |
{} |
| } |
|
81 - Globally optimal regions and boundaries as minimum ratio weight cycles.
I. H. Jermyn et H. Ishikawa. IEEE Trans. Pattern Analysis and Machine Intelligence, 23(10): pages 1075-1088, octobre 2001.
Mots-clés : Graphe, Ratio, Cycle, Segmentation, Minimum global.
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{jermyn_tpami01,
|
| author |
= |
{Jermyn, I. H. and Ishikawa, H.}, |
| title |
= |
{Globally optimal regions and boundaries as minimum ratio weight cycles}, |
| year |
= |
{2001}, |
| month |
= |
{octobre}, |
| journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
| volume |
= |
{23}, |
| number |
= |
{10}, |
| pages |
= |
{1075-1088}, |
| url |
= |
{http://dx.doi.org/10.1109/34.954599}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/jermyn_tpami01.pdf}, |
| keyword |
= |
{Graphe, Ratio, Cycle, Segmentation, Minimum global} |
| } |
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. |
|
82 - A RJMCMC algorithm for object processes in image processing.
X. Descombes et R. Stoica et L. Garcin et J. Zerubia. Monte Carlo Methods and Applications, 7(1-2): pages 149-156, 2001.
@ARTICLE{xd01c,
|
| author |
= |
{Descombes, X. and Stoica, R. and Garcin, L. and Zerubia, J.}, |
| title |
= |
{A RJMCMC algorithm for object processes in image processing}, |
| year |
= |
{2001}, |
| journal |
= |
{Monte Carlo Methods and Applications}, |
| volume |
= |
{7}, |
| number |
= |
{1-2}, |
| pages |
= |
{149-156}, |
| url |
= |
{http://www.degruyter.com/view/j/mcma.2001.7.issue-1-2/mcma.2001.7.1-2.149/mcma.2001.7.1-2.149.xml}, |
| keyword |
= |
{} |
| } |
|
83 - Image segmentation using Markov random field model in fully parallel cellular network architectures.
T. Szirányi et J. Zerubia et L. Czúni et D. Geldreich et Z. Kato. Real Time Imaging, 6(3): pages 195-211, juin 2000.
@ARTICLE{jz00y,
|
| author |
= |
{Szirányi, T. and Zerubia, J. and Czúni, L. and Geldreich, D. and Kato, Z.}, |
| title |
= |
{Image segmentation using Markov random field model in fully parallel cellular network architectures}, |
| year |
= |
{2000}, |
| month |
= |
{juin}, |
| journal |
= |
{Real Time Imaging}, |
| volume |
= |
{6}, |
| number |
= |
{3}, |
| pages |
= |
{195-211}, |
| pdf |
= |
{http://dx.doi.org/10.1006/rtim.1998.0159}, |
| keyword |
= |
{} |
| } |
Abstract :
Markovian approaches to early vision processes need a huge amount of computing power. These algorithms can usually be implemented on parallel computing structures. Herein, we show that the Markovian labeling approach can be implemented in fully parallel cellular network architectures, using simple functions and data representations. This makes possible to implement our model in parallel imaging VLSI chips.
As an example, we have developed a simplified statistical image segmentation algorithm for the Cellular Neural/Nonlinear Networks Universal Machine (CNN-UM), which is a new image processing tool, containing thousands of cells with analog dynamics, local memories and processing units. The Modified Metropolis Dynamics (MMD) optimization method can be implemented into the raw analog architecture of the CNN-UM. We can introduce the whole pseudo-stochastic segmentation process in the CNN architecture using 8 memories/cell. We use simple arithmetic functions (addition, multiplication), equality-test between neighboring pixels and very simple nonlinear output functions (step, jigsaw). With this architecture, the proposed VLSI CNN chip can execute a pseudo-stochastic relaxation algorithm of about 100 iterations in about 100 μs.
In the suggested solution the segmentation is unsupervised, where a pixel-level statistical estimation model is used. We have tested different monogrid and multigrid architectures.
In our CNN-UM model several complex preprocessing steps can be involved, such as texture-classification or anisotropic diffusion. With these preprocessing steps, our fully parallel cellular system may work as a high-level image segmentation machine, using only simple functions based on the close-neighborhood of a pixel. |
|
84 - A variational model for image classification and restoration.
C. Samson et L. Blanc-Féraud et G. Aubert et J. Zerubia. IEEE Trans. Pattern Analysis ans Machine Intelligence, 22(5): pages 460-472, mai 2000.
@ARTICLE{cs00,
|
| author |
= |
{Samson, C. and Blanc-Féraud, L. and Aubert, G. and Zerubia, J.}, |
| title |
= |
{A variational model for image classification and restoration}, |
| year |
= |
{2000}, |
| month |
= |
{mai}, |
| journal |
= |
{IEEE Trans. Pattern Analysis ans Machine Intelligence}, |
| volume |
= |
{22}, |
| number |
= |
{5}, |
| pages |
= |
{460-472}, |
| pdf |
= |
{http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=857003}, |
| keyword |
= |
{} |
| } |
|
85 - A Level Set Model for Image Classification.
C. Samson et L. Blanc-Féraud et G. Aubert et J. Zerubia. International Journal of Computer Vision, 40(3): pages 187-198, 2000.
@ARTICLE{cs00b,
|
| author |
= |
{Samson, C. and Blanc-Féraud, L. and Aubert, G. and Zerubia, J.}, |
| title |
= |
{A Level Set Model for Image Classification}, |
| year |
= |
{2000}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{40}, |
| number |
= |
{3}, |
| pages |
= |
{187-198}, |
| url |
= |
{http://link.springer.com/article/10.1023%2FA%3A1008183109594}, |
| keyword |
= |
{} |
| } |
|
86 - Mise en correspondance et recalage de graphes~: application aux réseaux routiers extraits d'un couple carte/image.
C. Hivernat et X. Descombes et S. Randriamasy et J. Zerubia. Traitement du Signal, 17(1): pages 21-32, 2000.
@ARTICLE{xd00,
|
| author |
= |
{Hivernat, C. and Descombes, X. and Randriamasy, S. and Zerubia, J.}, |
| title |
= |
{Mise en correspondance et recalage de graphes~: application aux réseaux routiers extraits d'un couple carte/image}, |
| year |
= |
{2000}, |
| journal |
= |
{Traitement du Signal}, |
| volume |
= |
{17}, |
| number |
= |
{1}, |
| pages |
= |
{21-32}, |
| url |
= |
{http://documents.irevues.inist.fr/handle/2042/2129}, |
| keyword |
= |
{} |
| } |
|
87 - Texture analysis through a Markovian modelling and fuzzy classification: Application to urban area Extraction from Satellite Images.
A. Lorette et X. Descombes et J. Zerubia. International Journal of Computer Vision, 36(3): pages 221-236, 2000.
@ARTICLE{xd00a,
|
| author |
= |
{Lorette, A. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Texture analysis through a Markovian modelling and fuzzy classification: Application to urban area Extraction from Satellite Images}, |
| year |
= |
{2000}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{36}, |
| number |
= |
{3}, |
| pages |
= |
{221-236}, |
| url |
= |
{http://dx.doi.org/10.1023/A:1008129103384}, |
| pdf |
= |
{http://dx.doi.org/10.1023/A:1008129103384}, |
| keyword |
= |
{} |
| } |
|
88 - Comparison of Filtering Methods for fMRI Datasets.
F. Kruggel et Y. Von Cramon et X. Descombes. NeuroImage, 10(5): pages 530-543, novembre 1999.
@ARTICLE{xd99d,
|
| author |
= |
{Kruggel, F. and Von Cramon, Y. and Descombes, X.}, |
| title |
= |
{Comparison of Filtering Methods for fMRI Datasets}, |
| year |
= |
{1999}, |
| month |
= |
{novembre}, |
| journal |
= |
{NeuroImage}, |
| volume |
= |
{10}, |
| number |
= |
{5}, |
| pages |
= |
{530-543}, |
| url |
= |
{http://www.sciencedirect.com/science/article/pii/S1053811999904901}, |
| keyword |
= |
{} |
| } |
|
89 - Some remarks on the equivalence between 2D and 3D classical snakes and geodesic active contours.
L. Blanc-Féraud et G. Aubert. International Journal of Computer Vision, 34(1): pages 19-28, septembre 1999.
@ARTICLE{lbf99a,
|
| author |
= |
{Blanc-Féraud, L. and Aubert, G.}, |
| title |
= |
{Some remarks on the equivalence between 2D and 3D classical snakes and geodesic active contours}, |
| year |
= |
{1999}, |
| month |
= |
{septembre}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{34}, |
| number |
= |
{1}, |
| pages |
= |
{19-28}, |
| url |
= |
{http://link.springer.com/article/10.1023%2FA%3A1008168219878}, |
| keyword |
= |
{} |
| } |
|
90 - Estimation of Markov Random Field prior parameters using Markov chain Monte Carlo Maximum Likelihood.
X. Descombes et R. Morris et J. Zerubia et M. Berthod. IEEE Trans. Image Processing, 8(7): pages 954-963, juillet 1999.
Mots-clés : Markov processes, Monte Carlo methods, Potts model, Image segmentation, Maximum likelihood estimation .
@ARTICLE{xd99c,
|
| author |
= |
{Descombes, X. and Morris, R. and Zerubia, J. and Berthod, M.}, |
| title |
= |
{Estimation of Markov Random Field prior parameters using Markov chain Monte Carlo Maximum Likelihood}, |
| year |
= |
{1999}, |
| month |
= |
{juillet}, |
| journal |
= |
{IEEE Trans. Image Processing}, |
| volume |
= |
{8}, |
| number |
= |
{7}, |
| pages |
= |
{954-963}, |
| pdf |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=16772&arnumber=772239&count=14&index=6}, |
| keyword |
= |
{Markov processes, Monte Carlo methods, Potts model, Image segmentation, Maximum likelihood estimation } |
| } |
Abstract :
Developments in statistics now allow maximum likelihood estimators for the parameters of Markov random fields (MRFs) to be constructed. We detail the theory required, and present an algorithm that is easily implemented and practical in terms of computation time. We demonstrate this algorithm on three MRF models-the standard Potts model, an inhomogeneous variation of the Potts model, and a long-range interaction model, better adapted to modeling real-world images. We estimate the parameters from a synthetic and a real image, and then resynthesize the models to demonstrate which features of the image have been captured by the model. Segmentations are computed based on the estimated parameters and conclusions drawn. |
|
91 - A Markov Pixon Information approach for low level image description.
X. Descombes et F. Kruggel. IEEE Trans. Pattern Analysis ans Machine Intelligence, 21(6): pages 482-494, juin 1999.
@ARTICLE{xd99b,
|
| author |
= |
{Descombes, X. and Kruggel, F.}, |
| title |
= |
{A Markov Pixon Information approach for low level image description}, |
| year |
= |
{1999}, |
| month |
= |
{juin}, |
| journal |
= |
{IEEE Trans. Pattern Analysis ans Machine Intelligence}, |
| volume |
= |
{21}, |
| number |
= |
{6}, |
| pages |
= |
{482-494}, |
| pdf |
= |
{http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=771311}, |
| keyword |
= |
{} |
| } |
|
92 - Non linear regularization for helioseismic inversions. Application for the study of the solar tachocline.
T. Corbard et L. Blanc-Féraud et G. Berthomieu et J. Provost. Astronomy and Astrophysics, (344): pages 696-708, 1999.
@ARTICLE{lbf99b,
|
| author |
= |
{Corbard, T. and Blanc-Féraud, L. and Berthomieu, G. and Provost, J.}, |
| title |
= |
{Non linear regularization for helioseismic inversions. Application for the study of the solar tachocline}, |
| year |
= |
{1999}, |
| journal |
= |
{Astronomy and Astrophysics}, |
| number |
= |
{344}, |
| pages |
= |
{696-708}, |
| url |
= |
{http://arxiv.org/abs/astro-ph/9901112}, |
| keyword |
= |
{} |
| } |
|
93 - GMRF Parameter Estimation in a non-stationary Framework by a Renormalization Technique: Application to Remote Sensing Imaging.
X. Descombes et M. Sigelle et F. Prêteux. IEEE Trans. Image Processing, 8(4): pages 490-503, 1999.
@ARTICLE{xd99a,
|
| author |
= |
{Descombes, X. and Sigelle, M. and Prêteux, F.}, |
| title |
= |
{GMRF Parameter Estimation in a non-stationary Framework by a Renormalization Technique: Application to Remote Sensing Imaging}, |
| year |
= |
{1999}, |
| journal |
= |
{IEEE Trans. Image Processing}, |
| volume |
= |
{8}, |
| number |
= |
{4}, |
| pages |
= |
{490-503}, |
| url |
= |
{https://hal.archives-ouvertes.fr/hal-00272393}, |
| keyword |
= |
{} |
| } |
|
94 - Unsupervised parallel image classification using Markovian models.
Z. Kato et J. Zerubia et M. Berthod. Pattern Recognition, 32(4): pages 591-604, 1999.
Mots-clés : Markov random field model, Hierarchical model, Parameter estimation, Parallel unsupervised image classification.
@ARTICLE{jz99a,
|
| author |
= |
{Kato, Z. and Zerubia, J. and Berthod, M.}, |
| title |
= |
{Unsupervised parallel image classification using Markovian models}, |
| year |
= |
{1999}, |
| journal |
= |
{Pattern Recognition}, |
| volume |
= |
{32}, |
| number |
= |
{4}, |
| pages |
= |
{591-604}, |
| pdf |
= |
{http://dx.doi.org/10.1016/S0031-3203(98)00104-6}, |
| keyword |
= |
{Markov random field model, Hierarchical model, Parameter estimation, Parallel unsupervised image classification} |
| } |
Abstract :
This paper deals with the problem of unsupervised classification of images modeled by Markov random fields (MRF). If the model parameters are known then we have various methods to solve the segmentation problem (simulated annealing (SA), iterated conditional modes (ICM), etc). However, when the parameters are unknown, the problem becomes more difficult. One has to estimate the hidden label field parameters only from the observed image. Herein, we are interested in parameter estimation methods related to monogrid and hierarchical MRF models. The basic idea is similar to the expectation–maximization (EM) algorithm: we recursively look at the maximum a posteriori (MAP) estimate of the label field given the estimated parameters, then we look at the maximum likelihood (ML) estimate of the parameters given a tentative labeling obtained at the previous step. The only parameter supposed to be known is the number of classes, all the other parameters are estimated. The proposed algorithms have been implemented on a Connection Machine CM200. Comparative experiments have been performed on both noisy synthetic data and real images. |
|
95 - Particle tracking with iterated Kalman filters and smoothers : the PMHT algorithm.
A. Strandlie et J. Zerubia. Computer Physics Communications, 123(1-3): pages 77-87, 1999.
@ARTICLE{jz99b,
|
| author |
= |
{Strandlie, A. and Zerubia, J.}, |
| title |
= |
{Particle tracking with iterated Kalman filters and smoothers : the PMHT algorithm}, |
| year |
= |
{1999}, |
| journal |
= |
{Computer Physics Communications}, |
| volume |
= |
{123}, |
| number |
= |
{1-3}, |
| pages |
= |
{77-87}, |
| url |
= |
{http://www.sciencedirect.com/science/article/pii/S0010465599002581}, |
| keyword |
= |
{} |
| } |
|
96 - A generalized sampling theory without bandlimiting constraints.
M. Unser et J. Zerubia. IEEE Trans. on Circuits And Systems II, 45(8): pages 959-969, août 1998.
@ARTICLE{jz98b,
|
| author |
= |
{Unser, M. and Zerubia, J.}, |
| title |
= |
{A generalized sampling theory without bandlimiting constraints}, |
| year |
= |
{1998}, |
| month |
= |
{août}, |
| journal |
= |
{IEEE Trans. on Circuits And Systems II}, |
| volume |
= |
{45}, |
| number |
= |
{8}, |
| pages |
= |
{959-969}, |
| pdf |
= |
{http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=718806}, |
| keyword |
= |
{} |
| } |
|
97 - Variational approach for edge preserving regularization using coupled PDE's.
S. Teboul et L. Blanc-Féraud et G. Aubert et M. Barlaud. IEEE Trans. Image Processing, 7(3): pages 387-397, mars 1998.
@ARTICLE{lbf98,
|
| author |
= |
{Teboul, S. and Blanc-Féraud, L. and Aubert, G. and Barlaud, M.}, |
| title |
= |
{Variational approach for edge preserving regularization using coupled PDE's}, |
| year |
= |
{1998}, |
| month |
= |
{mars}, |
| journal |
= |
{IEEE Trans. Image Processing}, |
| volume |
= |
{7}, |
| number |
= |
{3}, |
| pages |
= |
{387-397}, |
| pdf |
= |
{http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=661189}, |
| keyword |
= |
{} |
| } |
|
98 - Combined constraints for efficient algebraic regularized methods.
I. Laurette et J. Darcourt et L. Blanc-Féraud et P.M. Koulibaly et M. Barlaud. Physics in Medicine and Biology, 43(4): pages 991-1000, 1998.
@ARTICLE{lbf98a,
|
| author |
= |
{Laurette, I. and Darcourt, J. and Blanc-Féraud, L. and Koulibaly, P.M. and Barlaud, M.}, |
| title |
= |
{Combined constraints for efficient algebraic regularized methods}, |
| year |
= |
{1998}, |
| journal |
= |
{Physics in Medicine and Biology}, |
| volume |
= |
{43}, |
| number |
= |
{4}, |
| pages |
= |
{991-1000}, |
| url |
= |
{http://iopscience.iop.org/0031-9155/43/4/026}, |
| keyword |
= |
{} |
| } |
|
99 - fMRI Signal Restoration Using an Edge Preserving Spatio-temporal Markov Random Field.
X. Descombes et F. Kruggel et Y. von Cramon. NeuroImage, 8: pages 340-349, 1998.
Mots-clés : fMRI, Restauration, Champs de Markov.
Copyright : published in NeuroIMage by Elsevier
||http://www.elsevier.com/wps/find/homepage.cws_home
@ARTICLE{descombes98d,
|
| author |
= |
{Descombes, X. and Kruggel, F. and von Cramon, Y.}, |
| title |
= |
{fMRI Signal Restoration Using an Edge Preserving Spatio-temporal Markov Random Field}, |
| year |
= |
{1998}, |
| journal |
= |
{NeuroImage}, |
| volume |
= |
{8}, |
| pages |
= |
{340-349}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/1998_descombes98d.pdf}, |
| keyword |
= |
{fMRI, Restauration, Champs de Markov} |
| } |
|
100 - Spatio-temporal fMRI analysis using Markov Random Fields.
X. Descombes et F. Kruggel et Y. Von Cramon. IEEE Trans. Medical Imaging, 17(6): pages 1028-1039, 1998.
Note : à paraître.
Mots-clés : fMRI, Markov Random Fields.
@ARTICLE{descombes98,
|
| author |
= |
{Descombes, X. and Kruggel, F. and Von Cramon, Y.}, |
| title |
= |
{Spatio-temporal fMRI analysis using Markov Random Fields}, |
| year |
= |
{1998}, |
| journal |
= |
{IEEE Trans. Medical Imaging}, |
| volume |
= |
{17}, |
| number |
= |
{6}, |
| pages |
= |
{1028-1039}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Xavier.Descombes/publis_dr/TMI1.pdf}, |
| keyword |
= |
{fMRI, Markov Random Fields} |
| } |
|
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