Author, as appears in the article.: Latorre-Carmona, Pedro; Martinez Sotoca, Jose; Pla, Filiberto; Bioucas-Dias, Jose; Julia Ferre, Carme;
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: Julià Ferré, Maria Carmen
Keywords: Variable selection Regression Optimization Noise Models Land Imagery Hyperspectral datasets Feature selection Errors Classification
Abstract: This paper presents a comparative analysis of six band selection methods applied to hyperspectral datasets for biophysical variable estimation problems, where the effect of denoising on band selection performance has also been analyzed. In particular, we consider four hyperspectral datasets and three regressors of different nature (epsilon-SVR, Regression Trees, and Kernel Ridge Regression). Results show that the denoising approach improves the band selection quality of all the tested methods. We show that noise filtering is more beneficial for the selection methods that use an estimator based on the whole dataset for the prediction of the output than for methods that use strategies based on local information (neighboring points).
Thematic Areas: Saúde coletiva Remote sensing Planejamento urbano e regional / demografia Odontología Matemática / probabilidade e estatística Interdisciplinar Imaging science & photographic technology Geography, physical Geografía Geociências Engineering, electrical & electronic Engenharias iv Engenharias iii Engenharias i Computers in earth sciences Ciências ambientais Ciências agrárias i Ciência da computação Biodiversidade Atmospheric science
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: carme.julia@urv.cat
Author identifier: 0000-0003-3440-6175
Record's date: 2023-05-20
Papper version: info:eu-repo/semantics/acceptedVersion
Papper original source: Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. 6 (2): 473-481
APA: Latorre-Carmona, Pedro; Martinez Sotoca, Jose; Pla, Filiberto; Bioucas-Dias, Jose; Julia Ferre, Carme; (2013). Effect of Denoising in Band Selection for Regression Tasks in Hyperspectral Datasets. Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, 6(2), 473-481. DOI: 10.1109/JSTARS.2013.2241022
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Entity: Universitat Rovira i Virgili
Journal publication year: 2013
Publication Type: Journal Publications
Repositori URV