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Publications of Josiane Zerubia
Result of the query in the list of publications :
173 Conference articles |
62 - Parametric blind deconvolution for confocal laser scanning microscopy.
P. Pankajakshan and B. Zhang and L. Blanc-Féraud and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. 29th International Conference of IEEE EMBS (EMBC-07), pages 6531-6534, August 2007.
Keywords : Confocal microscopy, Blind Deconvolution, Poisson noise, Total variation, EM algorithm, Bayesian estimation.
Copyright : ©2007 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.
@INPROCEEDINGS{Pankajakshan07a,
|
| author |
= |
{Pankajakshan, P. and Zhang, B. and Blanc-Féraud, L. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Parametric blind deconvolution for confocal laser scanning microscopy}, |
| year |
= |
{2007}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. 29th International Conference of IEEE EMBS (EMBC-07)}, |
| pages |
= |
{6531-6534}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/4352184/4352185/04353856.pdf?tp=&isnumber=&arnumber=4353856}, |
| keyword |
= |
{Confocal microscopy, Blind Deconvolution, Poisson noise, Total variation, EM algorithm, Bayesian estimation} |
| } |
Abstract :
In this paper, we propose a method for the
iterative restoration of fluorescence Confocal Laser Scanning
Microscopic (CLSM) images and parametric estimation of the
acquisition system’s Point Spread Function (PSF). The CLSM is
an optical fluorescence microscope that scans a specimen in 3D
and uses a pinhole to reject most of the out-of-focus light. However,
the quality of the images suffers from two basic physical
limitations. The diffraction-limited nature of the optical system,
and the reduced amount of light detected by the photomultiplier
cause blur and photon counting noise respectively. These images
can hence benefit from post-processing restoration methods
based on deconvolution. An efficient method for parametric
blind image deconvolution involves the simultaneous estimation
of the specimen 3D distribution of fluorescent sources and
the microscope PSF. By using a model for the microscope
image acquisition physical process, we reduce the number of
free parameters describing the PSF and introduce constraints.
The parameters of the PSF may vary during the course of
experimentation, and so they have to be estimated directly from
the observed data. A priori model of the specimen is further
applied to stabilize the alternate minimization algorithm and to
converge to the solutions. |
|
63 - Assessment of different classification algorithms for burnt land discrimination.
O. Zammit and X. Descombes and J. Zerubia. In Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pages 3000-3003, Barcelone, Spain, July 2007.
Keywords : Satellite images, Burnt areas, Support Vector Machines, Forest fires, Classification.
Copyright : IEEE
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64 - A Hierarchical Texture Model for Unsupervised Segmentation of Remotely Sensed Images.
G. Scarpa and M. Haindl and J. Zerubia. In Scandinavian Conference on Image Analysis, Vol. 4522/2007, pages 303-312, series LNCS 4522, Ed. Springer Berlin / Heidelberg, Aalborg, Denmark, June 2007.
@INPROCEEDINGS{scarpa_scia_07,
|
| author |
= |
{Scarpa, G. and Haindl, M. and Zerubia, J.}, |
| title |
= |
{A Hierarchical Texture Model for Unsupervised Segmentation of Remotely Sensed Images}, |
| year |
= |
{2007}, |
| month |
= |
{June}, |
| booktitle |
= |
{Scandinavian Conference on Image Analysis}, |
| volume |
= |
{4522/2007}, |
| pages |
= |
{303-312}, |
| series |
= |
{LNCS 4522}, |
| editor |
= |
{Springer Berlin / Heidelberg}, |
| address |
= |
{Aalborg, Denmark}, |
| url |
= |
{http://link.springer.com/chapter/10.1007%2F978-3-540-73040-8_31}, |
| keyword |
= |
{} |
| } |
|
65 - Indexing Satellite Images with Features Computed from Man-Made Structures on the Earth’s Surface.
A. Bhattacharya and M. Roux and H. Maitre and I. H. Jermyn and X. Descombes and J. Zerubia. In Proc. International Workshop on Content-Based Multimedia Indexing, Bordeaux, France, June 2007.
Keywords : Indexation, Road network, Semantic, Retrieval, Feature statistics.
@INPROCEEDINGS{Bhattacharya07a,
|
| author |
= |
{Bhattacharya, A. and Roux, M. and Maitre, H. and Jermyn, I. H. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Indexing Satellite Images with Features Computed from Man-Made Structures on the Earth’s Surface}, |
| year |
= |
{2007}, |
| month |
= |
{June}, |
| booktitle |
= |
{Proc. International Workshop on Content-Based Multimedia Indexing}, |
| address |
= |
{Bordeaux, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Bhattacharya07a.pdf}, |
| keyword |
= |
{Indexation, Road network, Semantic, Retrieval, Feature statistics} |
| } |
Abstract :
Indexing and retrieval from remote sensing image databases relies on the extraction of appropriate information from the data about the entity of interest (e.g. land cover type) and on the robustness of this extraction to nuisance variables. Other entities in an image may be strongly correlated with the entity of interest and their properties can therefore be used to characterize this entity. The road network contained in an image is one example. The properties of road networks vary considerably from one geographical environment to another, and they can therefore be used to classify and retrieve such environments. In this paper, we define several such environments, and classify them with the aid of geometrical and topological features computed from the road networks occurring in them. The relative failure of network extraction methods in certain types of urban area obliges us to segment such areas and to add a second set of geometrical and topological features computed from the segmentations. To validate the approach, feature selection and SVM linear kernel classification are performed on the feature set arising from a diverse image database. |
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66 - A Hierarchical finite-state model for texture segmentation.
G. Scarpa and M. Haindl and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vol. 1, pages 1209-1212, Honolulu, HI (USA), April 2007.
@INPROCEEDINGS{scarpa_icassp_07,
|
| author |
= |
{Scarpa, G. and Haindl, M. and Zerubia, J.}, |
| title |
= |
{A Hierarchical finite-state model for texture segmentation}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| volume |
= |
{1}, |
| pages |
= |
{1209-1212}, |
| address |
= |
{Honolulu, HI (USA)}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4217303}, |
| keyword |
= |
{} |
| } |
|
67 - Urban road extraction from VHR images using a multiscale image model and a phase field model of network geometry.
T. Peng and I. H. Jermyn and V. Prinet and J. Zerubia. In Proc. Urban, Paris, France, April 2007.
Keywords : Road network, Very high resolution, Multiscale, Higher-order, Active contour, Shape.
@INPROCEEDINGS{Peng07_urban,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{Urban road extraction from VHR images using a multiscale image model and a phase field model of network geometry}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. Urban}, |
| address |
= |
{Paris, France}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Peng07urban.pdf}, |
| keyword |
= |
{Road network, Very high resolution, Multiscale, Higher-order, Active contour, Shape} |
| } |
Abstract :
This paper addresses the problem of automatically
extracting the main road network in a dense urban area from
a very high resolution optical satellite image using a variational
approach. The model energy has two parts: a phase field higherorder
active contour energy that describes our prior knowledge
of road network geometry, i.e. that it is composed of elongated
structures with roughly parallel borders that meet at junctions;
and a multi-scale statistical image model describing the image
we expect to see given a road network. By minimizing the model
energy, an estimate of the road network is obtained. Promising
results on 0.6m QuickBird Panchromatic images are presented,
and future improvements to the models are outlined. |
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68 - Circular object segmentation using higher-order active contours.
P. Horvath and I. H. Jermyn and Z. Kato and J. Zerubia. In In Proc. Conference of the Hungarian Association for Image Analysis and Pattern Recognition (KEPAF'07), Debrecen, Hungary, January 2007.
Note : In Hungarian
Keywords : Higher-order, Tree Crown Extraction, Shape.
@INPROCEEDINGS{Horvath07a,
|
| author |
= |
{Horvath, P. and Jermyn, I. H. and Kato, Z. and Zerubia, J.}, |
| title |
= |
{Circular object segmentation using higher-order active contours}, |
| year |
= |
{2007}, |
| month |
= |
{January}, |
| booktitle |
= |
{In Proc. Conference of the Hungarian Association for Image Analysis and Pattern Recognition (KEPAF'07)}, |
| address |
= |
{Debrecen, Hungary}, |
| note |
= |
{In Hungarian}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Horvath07a.pdf}, |
| keyword |
= |
{Higher-order, Tree Crown Extraction, Shape} |
| } |
|
69 - Wavelet-based restoration methods: application to 3D confocal microscopy images.
C. Chaux and L. Blanc-Féraud and J. Zerubia. In Proc. SPIE Conference on Wavelets, 2007.
Keywords : Restoration, Deconvolution, 3D images, Confocal microscopy, Poisson noise, Wavelets.
Copyright : Copyright 2007 Society of Photo-Optical Instrumentation Engineers.
This paper was published in Proc. SPIE Conference on Wavelets and is made available as an electronic reprint (preprint) with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
@INPROCEEDINGS{chaux2007,
|
| author |
= |
{Chaux, C. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Wavelet-based restoration methods: application to 3D confocal microscopy images}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Proc. SPIE Conference on Wavelets}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_chaux2007.pdf}, |
| keyword |
= |
{Restoration, Deconvolution, 3D images, Confocal microscopy, Poisson noise, Wavelets} |
| } |
|
70 - Vers une détection et une classification non-supervisées des changements inter-images.
A. Fournier and X. Descombes and J. Zerubia. In Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA), 2007.
Keywords : Markov Random Fields, Registration, Change detection, Clustering.
@INPROCEEDINGS{fournier-taima-07,
|
| author |
= |
{Fournier, A. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Vers une détection et une classification non-supervisées des changements inter-images}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA)}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_fournier-taima-07.pdf}, |
| keyword |
= |
{Markov Random Fields, Registration, Change detection, Clustering} |
| } |
|
71 - Tree Species Classification Using Radiometry, Texture and Shape Based Features.
M. S. Kulikova and M. Mani and A. Srivastava and X. Descombes and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), 2007.
Keywords : shape based features, SVM, tree classification.
@INPROCEEDINGS{Kulikova07,
|
| author |
= |
{Kulikova, M. S. and Mani, M. and Srivastava, A. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Tree Species Classification Using Radiometry, Texture and Shape Based Features}, |
| year |
= |
{2007}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| pdf |
= |
{http://hal.archives-ouvertes.fr/docs/00/46/55/05/PDF/Kulikova_EUSIPCO2007.pdf}, |
| keyword |
= |
{shape based features, SVM, tree classification} |
| } |
Abstract :
We consider the problem of tree species classification from high resolution aerial images based on radiometry, texture and a shape modeling. We use the notion of shape space proposed by Klassen et al., which provides a shape description invariant to translation, rotation and scaling. The shape features are extracted within a geodesic distance in the shape space. We then perform a classification using a SVM approach. We are able to show that the shape descriptors improve the classification performance relative to a classifier based on radiometric and textural descriptors alone. We obtain these results using high resolution Colour InfraRed (CIR) aerial images provided by the Swedish University of Agricultural Sciences. The image viewpoint is close to the nadir, i.e. the tree crowns are seen from above. |
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