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Détection de bateaux dans des images satellitaires optiques panchromatiques

Abstract : This paper presents the experimental results obtained for an automatic detection of ships in High Resolution optical satellite images. Our images are panchromatic SPOT 5 images, whose resolution is 5m per pixel. Our detection method is part of an industrial project of maritime surveillance. It is based on the Bayesian decision theory and does not need any preprocessing.The detection is composed of three stages. The first one is a pre-detection of targets that gives us candidates. The second one is a precise segmentation of each candidate. The third one is a classification of candidates into three classes : real small targets, real big targets and false alarms. The two first stages are based on the bayesian theory, using a very simple image model that leads to very fast algorithms. For now, the classification is based on multivariate decision tree. Finally, the overall results of the method are given for a set of images, as close as possible to the operational conditions and show the performances of the proposed method (detection of almost all the ships, false alarms due to crests of waves and an acceptable computing time).
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Contributor : Nadia Proia <>
Submitted on : Monday, June 20, 2011 - 7:16:06 PM
Last modification on : Wednesday, July 18, 2018 - 8:11:27 PM


  • HAL Id : hal-00601854, version 1



Nadia Proia, Vincent Pagé. Détection de bateaux dans des images satellitaires optiques panchromatiques. Journée Nationale de Photogrammétrie et Télédétection, May 2011, France. ⟨hal-00601854⟩



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