A Multirepresentational Fusion of Time Series for Pixelwise Classification
Dias, Danielle; Pinto, Allan; Dias, Ulisses; Lamparelli, Rubens; Le Maire, Guerric; Torres, Ricardo Da Silva
Peer reviewed, Journal article
Published version
Åpne
Permanent lenke
https://hdl.handle.net/11250/2994177Utgivelsesdato
2020Metadata
Vis full innførselSamlinger
- Institutt for IKT og realfag [555]
- Publikasjoner fra CRIStin - NTNU [37177]
Originalversjon
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020, 13 4399-4409. 10.1109/JSTARS.2020.3012117Sammendrag
This article addresses the pixelwise classification problem based on temporal profiles, which are encoded in 2-D representations based on recurrence plots, Gramian angular/ difference fields, and Markov transition field. We propose a multirepresentational fusion scheme that exploits the complementary view provided by those time series representations and different datadriven feature extractors and classifiers. We validate our ensemble scheme in the problem related to the classification of eucalyptus plantations in remote sensing images. Achieved results demonstrate that our proposal overcomes recently proposed baselines, and now represents the new state-of-the-art classification solution for the target dataset.