Title :
Is it possible to make pixel-based radar image classification user-friendly?
Author :
Pisani, R. ; Riedel, P. ; Gomes, A. ; Mizobe, R. ; Papa, J.
Author_Institution :
Geosci. & Exact Sci. Inst., UNESP-Univ. Estadual Paulista, Paulista, Brazil
Abstract :
In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in or- der to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed.
Keywords :
decision trees; geophysical image processing; image classification; learning (artificial intelligence); radar imaging; remote sensing by radar; image classification effectiveness; image classification efficiency; moist area classification; offline classification procedures; offline training procedures; online classification procedures; online training procedures; optimum-path forest; pattern recognition algorithms; pixel based radar image classification; training set pruning algorithm also; Accuracy; Machine learning; Prototypes; Radar imaging; Training; Vegetation; moist area classification; optimum-path forest; remote sensing;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4577-1003-2
DOI :
10.1109/IGARSS.2011.6050183
