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Abdourrahmane M. Atto

4 accepted papers

2024

Renyi Divergences Learning for explainable classification of SAR Image Pairs

ICASSP 2024accepted

We consider the problem of classifying a pair of Synthetic Aperture Radar (SAR) images by proposing an explainable and frugal algorithm that integrates a set of divergences. The approach relies on a statistical framework that takes standard probability distributions into account for modelling SAR da…

Cited by 0SourceScholar
2018

A Robust Change Detector for Highly Heterogeneous Multivariate Images

ICASSP 2018accepted

In this paper, we propose new detectors for Change Detection between two multivariate images. The data is supposed to fol-Iowa Compound Gaussian distribution. By using Likelihood Ratio Test (LRT) and Generalised LRT (GLRT) approaches, we derive our detectors. The CFAR behaviour has been studied and…

Cited by 0SourceScholar
2017

A subspace approach for shrinkage parameter selection in undersampled configuration for Regularised Tyler Estimators

ICASSP 2017accepted

Regularized Tyler Estimator's (RTE) have raised attention over the past years due to their attractive performance over a wide range of noise distributions and their natural robustness to outliers. Developing adaptive methods for the selection of the regularisation parameter α is currently an active…

Cited by 0SourceScholar
2017

Multivariate Linear Time-Frequency modeling and adaptive robust target detection in highly textured monovariate SAR image

ICASSP 2017accepted

Usually, in radar imaging, the scatterers are supposed to respond the same way regardless of the angle from which they are viewed and have the same properties within the emitted spectral bandwidth. Nevertheless, new capacities in SAR imaging (large bandwidth, large angular extent) make this assumpti…

Cited by 0SourceScholar