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The Publications
Result of the query in the list of publications :
245 Conference articles |
149 - Tree Crown Extraction using Marked Point Processes.
G. Perrin and X. Descombes and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), University of Technology, Vienna, Austria, September 2004.
Keywords : RJMCMC, Marked point process, Simulated Annealing, Tree Crown Extraction, Object extraction, Stochastic geometry.
@INPROCEEDINGS{perrin04a,
|
| author |
= |
{Perrin, G. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Tree Crown Extraction using Marked Point Processes}, |
| year |
= |
{2004}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{University of Technology, Vienna, Austria}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/perrin_eusipco2004.pdf}, |
| ps |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/perrin_eusipco2004.ps.gz}, |
| keyword |
= |
{RJMCMC, Marked point process, Simulated Annealing, Tree Crown Extraction, Object extraction, Stochastic geometry} |
| } |
Abstract :
In this paper we aim at extracting tree crowns from remotely sensed images. Our approach is to consider that these images are some realizations of a marked point process. The first step is to define the geometrical objects that design the trees, and the density of the process.
Then, we use a Reversible Jump Markov Chain Monte Carlo dynamics and a simulated annealing to get the maximum a posteriori estimator of the tree crown distribution on the image. Transitions of the Markov chain are managed by some specific proposition kernels.
Results are shown on aerial images of poplars provided by IFN. |
|
150 - Image Disocclusion Using a Probabilistic Gradient Orientation.
E. Villéger and G. Aubert and L. Blanc-Féraud. In Proc. International Conference on Pattern Recognition (ICPR), Cambridge, United Kingdom, August 2004.
@INPROCEEDINGS{Villeger04,
|
| author |
= |
{Villéger, E. and Aubert, G. and Blanc-Féraud, L.}, |
| title |
= |
{Image Disocclusion Using a Probabilistic Gradient Orientation}, |
| year |
= |
{2004}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Cambridge, United Kingdom}, |
| pdf |
= |
{http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1334034}, |
| keyword |
= |
{} |
| } |
|
151 - A Reversible Jump MCMC sampler for building detection in image processing.
M. Ortner and X. Descombes and J. Zerubia. In Monte Carlo Methods and Quasi-Monte Carlo Methods, series Special Se, Juan les Pins (France), June 2004.
@INPROCEEDINGS{mcmcqmc,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A Reversible Jump MCMC sampler for building detection in image processing}, |
| year |
= |
{2004}, |
| month |
= |
{June}, |
| booktitle |
= |
{Monte Carlo Methods and Quasi-Monte Carlo Methods}, |
| series |
= |
{Special Se}, |
| address |
= |
{Juan les Pins (France)}, |
| url |
= |
{http://link.springer.com/chapter/10.1007%2F3-540-31186-6_23}, |
| keyword |
= |
{} |
| } |
|
152 - A Bayesian Geometric Model for Line Network Extraction from Satellite Images.
C. Lacoste and X. Descombes and J. Zerubia and N. Baghdadi. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Montreal, Quebec, Canada, May 2004.
@INPROCEEDINGS{lacoste04a,
|
| author |
= |
{Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, |
| title |
= |
{A Bayesian Geometric Model for Line Network Extraction from Satellite Images}, |
| year |
= |
{2004}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Montreal, Quebec, Canada}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1326607}, |
| keyword |
= |
{} |
| } |
|
153 - A $l^1$-unified variational framework for image restoration.
J. Bect and L. Blanc-Féraud and G. Aubert and A. Chambolle. In Proc. European Conference on Computer Vision (ECCV), Vol. LNCS 3024, pages 1--13, Ed. T. Pajdla and J. Matas, Publ. Springer, Prague, Czech Republic, May 2004.
@INPROCEEDINGS{eccv04,
|
| author |
= |
{Bect, J. and Blanc-Féraud, L. and Aubert, G. and Chambolle, A.}, |
| title |
= |
{A $l^1$-unified variational framework for image restoration}, |
| year |
= |
{2004}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. European Conference on Computer Vision (ECCV)}, |
| volume |
= |
{LNCS 3024}, |
| pages |
= |
{1--13}, |
| editor |
= |
{T. Pajdla and J. Matas}, |
| publisher |
= |
{Springer}, |
| address |
= |
{Prague, Czech Republic}, |
| url |
= |
{http://link.springer.com/chapter/10.1007%2F978-3-540-24673-2_1}, |
| keyword |
= |
{} |
| } |
|
154 - Deconvolution in confocal microscopy with total variation regularization.
N. Dey and L. Blanc-Féraud and C. Zimmer and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. French-Danish Workshop on Spatial Statistics and Image Analysis in Biology (SSIAB), pages 117--120, May 2004.
@INPROCEEDINGS{Dey04b,
|
| author |
= |
{Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Deconvolution in confocal microscopy with total variation regularization}, |
| year |
= |
{2004}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. French-Danish Workshop on Spatial Statistics and Image Analysis in Biology (SSIAB)}, |
| pages |
= |
{117--120}, |
| url |
= |
{http://www3.jouy.inra.fr/miaj/public/imaste/ssiab2004/program/abw92/}, |
| keyword |
= |
{} |
| } |
|
155 - Texture analysis using probabilistic models of the unimodal and multimodal statistics of adaptative wavelet packet coefficients.
R. Cossu and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Montreal, Canada, May 2004.
Keywords : Bimodal, Adaptive, Wavelet packet, Texture, Gaussian mixture, Statistics.
@INPROCEEDINGS{cossu04a,
|
| author |
= |
{Cossu, R. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture analysis using probabilistic models of the unimodal and multimodal statistics of adaptative wavelet packet coefficients}, |
| year |
= |
{2004}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Montreal, Canada}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Cossu04icassp.pdf}, |
| keyword |
= |
{Bimodal, Adaptive, Wavelet packet, Texture, Gaussian mixture, Statistics} |
| } |
Abstract :
Although subband histograms of the wavelet coefficients of
natural images possess a characteristic leptokurtotic form,
this is no longer true for wavelet packet bases adapted to
a given texture. Instead, three types of subband statistics
are observed: Gaussian, leptokurtotic, and interestingly, in
some subbands, multimodal histograms. These subbands
are closely linked to the structure of the texture, and guarantee
that the most probable image is not flat. Motivated by
these observations, we propose a probabilistic model that
takes them into account. Adaptive wavelet packet subbands
are modelled as Gaussian, generalized Gaussian, or a constrained
Gaussian mixture. We use a Bayesian methodology,
finding MAP estimates for the adaptive basis, for subband
model selection, and for subband model parameters.
Results confirm the effectiveness of the proposed approach,
and highlight the importance of multimodal subbands for
texture discrimination and modelling. |
|
156 - A deconvolution method for confocal microscopy with total variation regularization.
N. Dey and L. Blanc-Féraud and C. Zimmer and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI), Arlington, USA, April 2004.
Keywords : 3D confocal microscopy, Poisson deconvolution, total variation regularization.
@INPROCEEDINGS{Dey04a,
|
| author |
= |
{Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{A deconvolution method for confocal microscopy with total variation regularization}, |
| year |
= |
{2004}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. IEEE International Symposium on Biomedical Imaging (ISBI)}, |
| address |
= |
{Arlington, USA}, |
| pdf |
= |
{http://dx.doi.org/10.1109/ISBI.2004.1398765}, |
| keyword |
= |
{3D confocal microscopy, Poisson deconvolution, total variation regularization} |
| } |
Abstract :
Confocal laser scanning microscopy is a powerful and increasingly popular technique for 3D imaging of biological specimens. However the acquired images are degraded by blur from out-of-focus light and Poisson noise due to photon-limited detection. Several deconvolution methods have been proposed to reduce these degradations, including the Richardson-Lucy algorithm, which computes a maximum likelihood estimation adapted to Poisson statistics. However this method tends to amplify noise if used without regularizing constraint. Here, we propose to combine the Richardson-Lucy algorithm with a regularizing constraint based on total variation, whose smoothing avoids oscillations while preserving edges. We show on simulated images that this constraint improves the deconvolution result both visually and using quantitative measures. |
|
157 - Marked Point Process in Image Analysis : from Context to Geometry.
X. Descombes and F. Kruggel and C. Lacoste and M. Ortner and G. Perrin and J. Zerubia. In International Conference on Spatial Point Process Modelling and its Application (SPPA), Castellon, Spain, 2004.
Keywords : RJMCMC, Object extraction, Marked point process, Stochastic geometry.
@INPROCEEDINGS{geostoch04a,
|
| author |
= |
{Descombes, X. and Kruggel, F. and Lacoste, C. and Ortner, M. and Perrin, G. and Zerubia, J.}, |
| title |
= |
{Marked Point Process in Image Analysis : from Context to Geometry}, |
| year |
= |
{2004}, |
| booktitle |
= |
{International Conference on Spatial Point Process Modelling and its Application (SPPA)}, |
| address |
= |
{Castellon, Spain}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/SPPA_2004.pdf}, |
| ps |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/SPPA_2004.ps.gz}, |
| keyword |
= |
{RJMCMC, Object extraction, Marked point process, Stochastic geometry} |
| } |
Abstract :
We consider the marked point process framework as a natural extension of the Markov random field approach in image analysis. We consider a general model defined by its density allowing us to consider some geometrical constraints on objects and between objects in feature extraction problems. Some examples are derived for small brain lesions detection from MR Images, road network, tree crown and building extraction from remotely sensed images. The results obtained on real data show the relevance of the proposal approach. |
|
158 - Extraction automatique de caricatures de bâtiments sur des Modèles Numériques d'Elèvation.
M. Ortner and X. Descombes and J. Zerubia. In Pixels et Cités, ENSG, Marne la Vallée, France, November 2003.
@INPROCEEDINGS{mathiaspix,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Extraction automatique de caricatures de bâtiments sur des Modèles Numériques d'Elèvation}, |
| year |
= |
{2003}, |
| month |
= |
{November}, |
| booktitle |
= |
{Pixels et Cités}, |
| address |
= |
{ENSG, Marne la Vallée, France}, |
| pdf |
= |
{Articles/PixelsCites2003.pdf}, |
| keyword |
= |
{} |
| } |
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