Skip to Main content Skip to Navigation
Conference papers

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.
Document type :
Conference papers
Complete list of metadata

Cited literature [16 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01188075
Contributor : Lionel Bombrun Connect in order to contact the contributor
Submitted on : Friday, August 28, 2015 - 2:36:45 PM
Last modification on : Friday, January 29, 2021 - 11:36:03 AM
Long-term archiving on: : Sunday, November 29, 2015 - 10:32:37 AM

File

Ilea15_IGARSS.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01188075, version 1

Citation

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. IEEE International Geoscience and Remote Sensing Symposium 2015, 2015, Milan, Italy. pp.3215-3218. ⟨hal-01188075⟩

Share

Metrics

Record views

282

Files downloads

388