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Statistical hypothesis test for maritime pine forest SAR images classification based on the geodesic distance

Abstract : This paper introduces a new statistical hypothesis test for image classification based on the geodesic distance. We present how it can be used for the classification of texture image. The proposed method is then employed for the classification of Polarimetric Synthetic Aperture Radar images of maritime pine forests on both simulated data with the PolSARproSim software and real data acquired during the ONERA RAMSES campaign in 2004.
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https://hal.inrae.fr/hal-02740462
Contributor : Migration Prodinra <>
Submitted on : Tuesday, June 2, 2020 - 11:08:39 PM
Last modification on : Wednesday, September 22, 2021 - 10:17:40 AM

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Ioana Ilea, Lionel Bombrun, Christian Germain, Isabelle Champion, Romulus Terebes, et al.. Statistical hypothesis test for maritime pine forest SAR images classification based on the geodesic distance. IGARSS 2015, Remote sensing: understanding the Earth for a safer world, IEEE Geoscience and Remote Sensing Society (GRSS). USA., Jul 2015, Milan, Italy. ⟨10.1109/IGARSS.2015.7326502⟩. ⟨hal-02740462⟩

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