1 - Object extraction from high resolution SAR images using a birth and death dynamics.
F. Arslan and X. Descombes and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Cairo, Egypt, November 2009.
Keywords : High resolution SAR images, Object extraction, Marked point process, birth and death process.
@INPROCEEDINGS{Fatih09,
|
| 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 |
= |
{November}, |
| 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, Object extraction, Marked point process, 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. |
|
top of the page
New demo webpage
get the bibtex
