González Bascoy, PedroQuesada Barriuso, PabloBlanco Heras, DoraArgüello Pedreira, Francisco2021-03-052021-03-052019Pedro G. Bascoy, Pablo Quesada-Barriuso, Dora B. Heras and Fancisco Argüello (2019) Wavelet-Based Multicomponent Denoising Profile for the Classification of Hyperspectral Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12 (2), 722 - 733. Doi: 10.1109/JSTARS.2019.28929901939-1404http://hdl.handle.net/10347/24654The high resolution of the hyperspectral remote sensing images available allows the detailed analysis of even small spatial structures. As a consequence, the study of techniques to efficiently extract spatial information is a very active realm. In this paper, we propose a novel denoising wavelet-based profile for the extraction of spatial information that does not require parameters fixed by the user. Over each band obtained by a wavelet-based feature extraction technique, a denoising profile (DP) is built through the recursive application of discrete wavelet transforms followed by a thresholding process. Each component of the DP consists of features reconstructed by recursively applying inverse wavelet transforms to the thresholded coefficients. Several thresholding methods are explored. In order to show the effectiveness of the extended DP (EDP), we propose a classification scheme based on the computation of the EDP and supervised classification by extreme learning machine. The obtained results are compared to other state-of-the-art methods based on profiles in the literature. An additional study of behavior in the presence of added noise is also performed showing the high reliability of the EDP proposedeng© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksClassificationDenoisingProfileRemote sensingWavelet transformjournal article10.1109/JSTARS.2019.28929902151-1535open access