Publications of Elena Zhizhina

Result of the query in the list of publications :

• 6 Articles
• 4 Conference articles
• 2 Technical and Research Reports

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6 Articles

1 - A Marked Point Process Model Including Strong Prior Shape Information Applied to Multiple Object Extraction From Images. M. S. Kulikova and I. H. Jermyn and X. Descombes and E. Zhizhina and J. Zerubia. International Journal of Computer Vision and Image Processing, 1(2): pages 1-12, 2011. Keywords : Active contour, Marked point process, multiple birth-and-death dynamics, multiple object extraction, Shape prior. @ARTICLE{kulikova_ijcvip2010, author = {Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, title = {A Marked Point Process Model Including Strong Prior Shape Information Applied to Multiple Object Extraction From Images}, year = {2011}, journal = {International Journal of Computer Vision and Image Processing}, volume = {1}, number = {2}, pages = {1-12}, url = {http://hal.archives-ouvertes.fr/hal-00804118}, keyword = {Active contour, Marked point process, multiple birth-and-death dynamics, multiple object extraction, Shape prior} } Abstract : Object extraction from images is one of the most important tasks in remote sensing image analysis. For accurate extraction from very high resolution (VHR) images, object geometry needs to be taken into account. A method for incorporating strong yet flexible prior shape information into a marked point process model for the extraction of multiple objects of complex shape is presented. To control the computational complexity, the objects considered are defined using the image data and the prior shape information. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process on the space of multiple objects. The authors present several experimental results on the extraction of tree crowns from VHR aerial images.

2 - A Point Process for Fully Automatic Road Network Detection in Satellite and Aerial Images. P. Cariou and X. Descombes and E. Zhizhina. Problems of Information Transmission, 10(3): pages 247-256, 2010. Keywords : Marked point process, birth and death process, Road network extraction. @ARTICLE{cariou2010, author = {Cariou, P. and Descombes, X. and Zhizhina, E.}, title = {A Point Process for Fully Automatic Road Network Detection in Satellite and Aerial Images}, year = {2010}, journal = {Problems of Information Transmission}, volume = {10}, number = {3}, pages = {247-256}, url = { http://www.jip.ru/2010/247-256-2010.pdf}, keyword = {Marked point process, birth and death process, Road network extraction} }

3 - Object Extraction Using a Stochastic Birth-and-Death Dynamics in Continuum. X. Descombes and R. Minlos and E. Zhizhina. Journal of Mathematical Imaging and Vision, 33(3): pages 347-359, 2009. Keywords : birth and death process, Marked point process, Object extraction. Copyright : Springer @ARTICLE{DZM08, author = {Descombes, X. and Minlos, R. and Zhizhina, E.}, title = {Object Extraction Using a Stochastic Birth-and-Death Dynamics in Continuum}, year = {2009}, journal = {Journal of Mathematical Imaging and Vision}, volume = {33}, number = {3}, pages = {347-359}, pdf = {http://dx.doi.org/10.1007/s10851-008-0117-y}, keyword = {birth and death process, Marked point process, Object extraction} } Abstract : We define a new birth and death dynamics dealing with configurations of disks in the plane. We prove the convergence of the continuous process and propose a discrete scheme converging to the continuous case. This framework is developed to address image processing problems consisting in detecting a configuration of objects from a digital image. The derived algorithm is applied for tree crown extraction and bird detection from aerial images. The performance of this approach is shown on real data.

4 - The Gibbs fields approach and related dynamics in image processing. X. Descombes and E. Zhizhina. Condensed Matter Physics, 11(2(54)): pages 293-312, 2008. Copyright : Institute for Condensed Matter @ARTICLE{LNA08, author = {Descombes, X. and Zhizhina, E.}, title = {The Gibbs fields approach and related dynamics in image processing}, year = {2008}, journal = {Condensed Matter Physics}, volume = {11}, number = {2(54)}, pages = {293-312}, keyword = {} }

5 - Applications of Gibbs fields methods to image processing problems. X. Descombes and E. Zhizhina. Problems of Information Transmission, 40(3): pages 108--125, September 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 = {September}, 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 = {} }

6 - Applications of Gibbs fields methods to image processing problems. X. Descombes and E. Zhizhina. Problems of Information Transmission, 40(3): pages 279-295, September 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 = {September}, 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 = {} }

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4 Conference articles

1 - Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours. M. S. Kulikova and I. H. Jermyn and X. Descombes and E. Zhizhina and J. Zerubia. In Proc. IS&T/SPIE Electronic Imaging, San Jose, USA, January 2010. Keywords : Object extraction, Marked point process, Shape prior, Active contour, birth-and-death dynamics. Copyright : Copyright 2010 by SPIE and IS&T. This paper was published in the proceedings of IS&T/SPIE Electronic Imaging 2010 Conference in San Jose, USA, and is made available as an electronic reprint with permission of SPIE and IS&T. 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{Kulikova10a, author = {Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, title = {Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours}, year = {2010}, month = {January}, booktitle = {Proc. IS&T/SPIE Electronic Imaging}, address = {San Jose, USA}, pdf = {http://hal.archives-ouvertes.fr/docs/00/46/54/72/PDF/Kulikova_SPIE2010.pdf}, keyword = {Object extraction, Marked point process, Shape prior, Active contour, birth-and-death dynamics} } Abstract : We extend the marked point process models that have been used for object extraction from images to arbitrarily shaped objects, without greatly increasing the computational complexity of sampling and estimation. From an alternative point of view, the approach can be viewed as an extension of the active contour methodology to an a priori unknown number of objects. Sampling and estimation are based on a stochastic birth-and-death process defined on the configuration space of an arbitrary number of objects, where the objects are defined by the image data and prior information. The performance of the approach is demonstrated via experimental results on synthetic and real data.

2 - A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects. M. S. Kulikova and I. H. Jermyn and X. Descombes and E. Zhizhina and J. Zerubia. In Proc. IEEE SITIS, Publ. IEEE Computer Society, Marrakech, Maroc, December 2009. Keywords : Object extraction, Marked point process, Shape prior, Active contour, multiple birth-and-death dynamics. @INPROCEEDINGS{Kulikova09a, author = {Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, title = {A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects}, year = {2009}, month = {December}, booktitle = {Proc. IEEE SITIS}, publisher = {IEEE Computer Society}, address = {Marrakech, Maroc}, pdf = {http://hal.inria.fr/docs/00/43/63/20/PDF/PID1054029.pdf}, keyword = {Object extraction, Marked point process, Shape prior, Active contour, multiple birth-and-death dynamics} } Abstract : We define a method for incorporating strong prior shape information into a recently extended Markov point process model for the extraction of arbitrarily-shaped objects from images. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process defined in a space of multiple objects. The single objects considered are defined by both the image data and the prior information in a way that controls the computational complexity of the estimation problem. The method is tested via experiments on a very high resolution aerial image of a scene composed of tree crowns.

3 - Reconstruction 3D du bâti par la technique des ombres chinoises. P. Lukashevish and A. Kraushonak and X. Descombes and J.D. Durou and B. Zalessky and E. Zhizhina. In GRETSI Dijon, Dijon, France, November 2009. Keywords : 3D reconstruction. @INPROCEEDINGS{luka09, author = {Lukashevish, P. and Kraushonak, A. and Descombes, X. and Durou, J.D. and Zalessky, B. and Zhizhina, E.}, title = {Reconstruction 3D du bâti par la technique des ombres chinoises}, year = {2009}, month = {November}, booktitle = {GRETSI Dijon}, address = {Dijon, France}, url = {http://hal.inria.fr/inria-00399208/fr/}, keyword = {3D reconstruction} }

4 - Image deconvolution using a stochastic differential equation approach. X. Descombes and M. Lebellego and E. Zhizhina. In Proc. nternational Conference on Computer Vision Theory and Applications, Barcelona, Spain, March 2007. Keywords : Deconvolution, Stochastic Differential Equation. @INPROCEEDINGS{xavBarca2, author = {Descombes, X. and Lebellego, M. and Zhizhina, E.}, title = {Image deconvolution using a stochastic differential equation approach}, year = {2007}, month = {March}, booktitle = {Proc. nternational Conference on Computer Vision Theory and Applications}, address = {Barcelona, Spain}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/2007_xavBarca2.pdf}, keyword = {Deconvolution, Stochastic Differential Equation} }

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2 Technical and Research Reports

1 - Object extraction using a stochastic birth-and-death dynamics in continuum. X. Descombes and R. Minlos and E. Zhizhina. Research Report 6135, INRIA, 2007. Keywords : birth and death process, Stochastic modeling, Wavelets. @TECHREPORT{RR-6135, author = {Descombes, X. and Minlos, R. and Zhizhina, E.}, title = {Object extraction using a stochastic birth-and-death dynamics in continuum}, year = {2007}, institution = {INRIA}, type = {Research Report}, number = {6135}, url = {https://hal.inria.fr/inria-00133726}, pdf = {http://hal.inria.fr/inria-00133726}, keyword = {birth and death process, Stochastic modeling, Wavelets} } Abstract : We define a new birth and death dynamics dealing with configurations of discs in the plane. We prove the convergence of the continuous process and propose a discrete scheme converging to the continuous case. This framework is developed to address image processing problems consisting in extracting objects. The derived algorithm is applied for tree crown extraction and bird detection from aerial images. The performance of this approach is shown on real data.

2 - Image Denoising using Stochastic Differential Equations. X. Descombes and E. Zhizhina. Research Report 4814, INRIA, France, May 2003. Keywords : Denoising. @TECHREPORT{4814, author = {Descombes, X. and Zhizhina, E.}, title = {Image Denoising using Stochastic Differential Equations}, year = {2003}, month = {May}, institution = {INRIA}, type = {Research Report}, number = {4814}, address = {France}, url = {https://hal.inria.fr/inria-00071772}, pdf = {https://hal.inria.fr/file/index/docid/71772/filename/RR-4814.pdf}, ps = {https://hal.inria.fr/docs/00/07/17/72/PS/RR-4814.ps}, keyword = {Denoising} } Résumé : Ce rapport concerne le problème de la restauration d'image avec une approche par Équation Différentielle Stochastique. Nous considérons un processus de diffusion convergeant vers une mesure de Gibbs. L'hamiltonien de la mesure de Gibbs contient un terme d'interactions, apportant des contraintes de lissage sur la solution, et un terme d'attache aux données. Nous étudions deux schémas d'approximation discrète de la dynamique de Langevin associée à ce processus de diffusion : les approximation d'Euler et explicite forte de Taylor. La vitesse de convergence des algorithmes correspondants est comparée à celle de l'algorithme de Metropolis-Hasting. Des résultats sont montrés sur des images de synthèse et réelles. Il montrent la supériorité de l'approche proposée lorsque l'on considère un faible nombre d'itérations. Abstract : We address the problem of image denoising using a Stochastic Differential Equation approach. We consider a diffusion process which converges to a Gibbs measure. The Hamiltonian of the Gibbs measure embeds an interaction term, providing smoothing properties, and a data term. We study two discrete approximations of the Langevin dynamics associated with this diffusion process: the Euler and the Explicit Strong Taylor approximations. We compare the convergence speed of the associated algorithms and the Metropolis-Hasting algorithm. Results are shown on synthetic and real data. They show that the proposed approach provides better results when considering a small number of iterations.

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