Title :
Multispectral Image Classification Using Multilayer Perceptron and Principal Components Analysis
Author :
da Silva, Wanessa ; Habermann, Mateus ; Hideiti Shiguemori, Elcio ; do Livramento Andrade, Leidiane ; Morgado de Castro, Ruy
Author_Institution :
Div. de Geointeligencia, Inst. de Estudos Avancados-IEAv, São José dos Campos, Brazil
Abstract :
This work presents a methodology for pattern classification from multispectral images acquired by the HSS airborne sensor. In order to achieve this purpose, a conjunction of Artificial Neural Network and Principal Components Analysis has been used. The results indicate that this approach can be alternatively employed in multispectral images to separate materials with specific characteristics based on their reflectance properties.
Keywords :
geophysical image processing; image classification; multilayer perceptrons; principal component analysis; reflectivity; HSS airborne sensor; artificial neural network; multilayer perceptron; multispectral image classification; pattern classification; principal component analysis; reflectance properties; Artificial neural networks; Asphalt; Concrete; Principal component analysis; Remote sensing; Soil; Vectors; artificial neural network; hyperspectral scanner system; multispectral image; principal components analysis;
Conference_Titel :
Computational Intelligence and 11th Brazilian Congress on Computational Intelligence (BRICS-CCI & CBIC), 2013 BRICS Congress on
Conference_Location :
Ipojuca
DOI :
10.1109/BRICS-CCI-CBIC.2013.98
