DJERMOUNE , El-Hadi

This paper combines supervised linear unmixing and deconvolution problems to increase the resolution of the abundance maps for industrial imaging systems. The joint unmixing-deconvolution (JUD) algorithm is introduced based on the Tikhonov regularization criterion for offline processing. In order to meet the needs of industrial applications,...

This paper proposes a joint supervised linear unmixing and deconvolution algorithm (JUD) to increase the resolution of the abundance maps for industrial imaging systems. The JUD algorithm is introduced based on a Tikhonov regularization criterion for offline processing. In order to meet the needs of industrial applications, the proposed JUD is...

This paper introduces a framework based on the LMS algorithm for sequential deconvolution of hyperspectral images acquired by industrial pushbroom imaging systems. Considering a sequential model of image blurring phenomenon, we derive a sliding-block zero-attracting LMS algorithm with spectral regularization. The role of each hyper-parameter is...

Hyperspectral imaging has received considerable attention in the last decade as it combines the power of digital imaging and spectroscopy. Every pixel in a hyperspectral image provides local spectral information about a scene of interest across a large number of contiguous bands. Several sensing techniques have been devised for hyperspectral...

Cet article s'intéresse à la conception d'une méthode séquentielle de déconvolution d'images hyperspectrales acquises par un imageur pushbroom. À partir de l'écriture sous forme séquentielle de l'image floutée, on propose un algorithme de type LMS (least mean squares) par bloc glissant qui inclut des termes de régularisation spatiale et...

This paper proposes a hyperspectral image deconvolution algorithm for the online restoration of hyperspectral images as provided by wiskbroom and pushbroom scanning systems. We introduce a least-mean-squares (LMS)-based framework accounting for the convolution kernel non-causality and including non-quadratic (zero attracting and piece-wise...

This paper proposes a hyperspectral image deconvolution algorithm for the online restoration of hyperspectral images as provided by wiskbroom and pushbroom scanning systems. We introduce a least-mean-squares (LMS)-based framework accounting for the convolution kernel non-causality and including non-quadratic (zero attracting and piece-wise...