Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-4/W19, 309-312, 2011
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-4-W19/309/2011/
doi:10.5194/isprsarchives-XXXVIII-4-W19-309-2011
© Author(s) 2011. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
07 Sep 2012
MAXIMUM LIKELIHOOD CLASSIFICATION OF HIGH-RESOLUTION SAR IMAGES IN URBAN AREA
M. Soheili Majd, E. Simonetto, and L. Polidori L2G JE 2508, IRSTV FR CNRS 2488, ESGT, 1 Bd Pythagore, 72000 Le Mans, France
Keywords: SAR, Urban area, supervised classification, Maximum–Likelihood Abstract. In this work, we propose a state-of-the-art on statistical analysis of polarimetric synthetic aperture radar (SAR) data, through the modeling of several indices. We concentrate on eight ground classes which have been carried out from amplitudes, co-polarisation ratio, depolarization ratios, and other polarimetric descriptors. To study their different statistical behaviours, we consider Gauss, log- normal, Beta I, Weibull, Gamma, and Fisher statistical models and estimate their parameters using three methods: method of moments (MoM), maximum-likelihood (ML) methodology, and log-cumulants method (MoML). Then, we study the opportunity of introducing this information in an adapted supervised classification scheme based on Maximum–Likelihood and Fisher pdf. Our work relies on an image of a suburban area, acquired by the airborne RAMSES SAR sensor of ONERA. The results prove the potential of such data to discriminate urban surfaces and show the usefulness of adapting any classical classification algorithm however classification maps present a persistant class confusion between flat gravelled or concrete roofs and trees.
Conference paper (PDF, 5319 KB)


Citation: Soheili Majd, M., Simonetto, E., and Polidori, L.: MAXIMUM LIKELIHOOD CLASSIFICATION OF HIGH-RESOLUTION SAR IMAGES IN URBAN AREA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-4/W19, 309-312, doi:10.5194/isprsarchives-XXXVIII-4-W19-309-2011, 2011.

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