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Theses

Surveillance maritime par analyse d'images satellitaires optiques panchromatiques

Abstract : The research presented in this thesis aims at determining the possibility of partial or total automatic ship detection in High Resolution optical satellite images. At first, we expose the industrial context of our study, which fixes the constraints in terms of performances and processing time. Then, we present the available satellite data for our study (SPOT 5 panchromatic images of 5m per pixel resolution). Then we detail our approach for ship detection : the first stage is a pre-detection of targets that gives us candidates. The second stage is a precise segmentation of each candidate and the third stage is a classification of candidates. Our pre-detection method is based on the Bayesian decision theory. This pre-detection supplies a set of regions of interests (ROI). Among them, we have ships, but also false alarms due to clouds and to crests of waves. The purpose of the following stage is to eliminate the false alarms and to characterize the pre-detected ships. Then, we detail the method used to segment candidates. It uses active contours and also uses the Bayesian decision theory. After a brief description of the characteristics extracted for the classication of ships, we present the classifier that we used. We complete the ship characterization by presenting two methods of wave ship detection. The first approach uses active contours and the second is based on an a contrario approach. We compare the results of these two approaches. To complete the study and replace it in the industrial and operational context, we present experiments of the complete algorithm on complete images to estimate the performances and the processing time of the whole method.
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Submitted on : Thursday, January 27, 2011 - 1:43:57 PM
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Nadia Proia. Surveillance maritime par analyse d'images satellitaires optiques panchromatiques. Informatique [cs]. Université des Antilles-Guyane, 2010. Français. ⟨tel-00560119⟩

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