A regularized sparse approximation method for hyperspectral image classificationReport as inadecuate




A regularized sparse approximation method for hyperspectral image classification - Download this document for free, or read online. Document in PDF available to download.

1 CRAN - Centre de Recherche en Automatique de Nancy 2 LCPME - Laboratoire de Chimie Physique et Microbiologie pour l-Environnement

Abstract : This paper presents a new technique for hyperspectral images classification based on simultaneous sparse approximation. The proposed approach consists in formulating the problem as a convex multi-objective optimization problem which incorporates a term favoring the simultaneous sparsity of the estimated coefficients and a term enforcing a regularity constraint along the rows of the coefficient matrix. We show that the optimization problem can be solved efficiently using FISTA Fast Iterative Shrinkage-Thresholding Algorithm. This approach is applied to a wood wastes classification problem using NIR hyperspectral images.

Keywords : Hyperspectral image classification simultaneous sparse approximation regularization constraint FISTA





Author: Leila Belmerhnia - El-Hadi Djermoune - David Brie - Cédric Carteret -

Source: https://hal.archives-ouvertes.fr/



DOWNLOAD PDF




Related documents