Artículos de revistas
Fine-Tuning Contextual-Based Optimum-Path Forest for Land-Cover Classification
Fecha
2016-05-01Registro en:
Ieee Geoscience And Remote Sensing Letters. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 13, n. 5, p. 735-739, 2016.
1545-598X
10.1109/LGRS.2016.2541458
WOS:000375274700026
WOS000375274700026.pdf
Autor
Universidade Federal de São Carlos (UFSCar)
Universidade Estadual Paulista (Unesp)
Institución
Resumen
Contextual-based learning aims at considering neighboring pixels to improve pixelwise-oriented classification techniques. In this letter, we presented a metaheuristic framework for the optimization of nondiscrete Markovian models considering the optimum-path forest (OPF) classifier, and we proposed a post-processing procedure to avoid overcorrection over high-frequency regions. The proposed approach outperformed previous results obtained with standard OPF in satellite imagery.