Technical Program

Paper Detail

Paper:IMDSP-P10.5
Session:Image Analysis
Time:Thursday, May 20, 15:30 - 17:30
Presentation: Poster
Topic: Image and Multidimensional Signal Processing: Image and Video Analysis
Title: A BAYESIAN GEOMETRIC MODEL FOR LINE NETWORK EXTRACTION FROM SATELLITE IMAGES
Authors: Caroline Lacoste; INRIA 
 Xavier Descombes; INRIA 
 Josiane Zerubia; INRIA 
 Nicolas Baghdadi; BRGM 
Abstract: This paper presents a two-steps algorithm to perform an unsupervised extraction of line networks from satellite images,within a stochastic geometry framework. First, we propose a new operator providing a measure of the possibility of linear structure presence on each image pixel. Second, we propose a Bayesian model in order to extract the line network from the operator output. The prior model, a Markov object process, incorporates the topological properties of the network through interactions between objects, while the line operator answers are taken into account in the likelihood. Optimization is realized by simulated annealing using a RJMCMC algorithm. An application to hydrographic network extraction is presented.
 
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