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Conference Papers Year : 2019

A new clustering algorithm for PolSAR images segmentation


This paper deals with polarimetric synthetic aperture radar (PolSAR) image segmentation. More precisely, we present a new robust clustering algorithm designed for non-Gaussian data. The algorithm is based on an expectation-maximization approach. Its novelty is that, in addition to the estimation of each cluster center and covariance matrix, it also provides for each observation an estimation of the scale parameter , allowing a better flexibility when assigning each observation in one cluster. The method performances are evaluated on both simulated and real multi-looked PolSAR data. It is demonstrated that the algorithm outperforms the classical clustering algorithms such as k-means and GMM (Gaussian-based EM algorithm) in various scenarios.
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Dates and versions

hal-02485766 , version 1 (20-02-2020)



Violeta Roizman, Gordana Draskovic, Frédéric Pascal. A new clustering algorithm for PolSAR images segmentation. 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019), Dec 2019, Guadeloupe, West Indies, France. ⟨10.1109/camsap45676.2019.9022495⟩. ⟨hal-02485766⟩
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