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Fatih Arslan
Ancien Stagiaire Master, Bogazici University, Istanbul
Contact :
E-Mail : | | FatihdotArslanatinriadotfr | Téléphone : | | (33)4-92-38- | Fax : | | (33)4-92-38-76-43 | Adresse : | | INRIA Sophia Antipolis
2004, route des Lucioles
06902 Sophia Antipolis Cedex
France |
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| Dernières publications dans le projet Ariana :
Object extraction from high resolution SAR images using a birth and death dynamics. F. Arslan et X. Descombes et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Cairo, Egypt, novembre 2009. Mots-clés : High resolution SAR images, Extraction d'objets, Processus ponctuels marques, birth and death process.
@INPROCEEDINGS{Fatih09,
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author |
= |
{Arslan, F. and Descombes, X. and Zerubia, J.}, |
title |
= |
{Object extraction from high resolution SAR images using a birth and death dynamics}, |
year |
= |
{2009}, |
month |
= |
{novembre}, |
booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
address |
= |
{Cairo, Egypt}, |
url |
= |
{http://dx.doi.org/10.1109/ICIP.2009.5413907}, |
keyword |
= |
{High resolution SAR images, Extraction d'objets, Processus ponctuels marques, birth and death process} |
} |
Abstract :
We present a new approach to extract predefined objects, such as trees and oil tanks for instance, from high resolution SAR images. We consider a stochastic approach based on an object process also called marked point process. The objects represent trees or oil tanks which are modeled by disks in the image. We first define a Gibbs density that takes into account both prior information and the data. The energy we define is composed of two terms, one is a prior, penalizing overlaps between objects, and the other is a data term, which measures the suitability of an object in the SAR image. The problem is then reduced to an energy minimization problem. We sample the process to extract the configuration of objects minimizing the energy by a fast birth-and-death dynamics, leading to the total number of objects (trees or oil tanks in our case). This approach is much faster than manual counts and does not need any preprocessing or supervision of a user. |
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Liste complète des publications dans le projet Ariana
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