[PDF][PDF] Hyperspectral image classification using spatial and spectral features
TAM Devi, N Rekha - International Journal of Scientific and …, 2013 - academia.edu
TAM Devi, N Rekha
International Journal of Scientific and Engineering Research, 2013•academia.eduClassification of hyperspectral remote sensing data with support vector machines (SVMs) is
investigated. Hyper spectral image classification techniques that use both spectral and
spatial information are more suitable, effective, and robust than those that use only spectral
information. The Features employed in this include Morphological profiles, Grey level
cooccurence matrix, Discrete Wavelet
investigated. Hyper spectral image classification techniques that use both spectral and
spatial information are more suitable, effective, and robust than those that use only spectral
information. The Features employed in this include Morphological profiles, Grey level
cooccurence matrix, Discrete Wavelet
Abstract
Classification of hyperspectral remote sensing data with support vector machines (SVMs) is investigated. Hyper spectral image classification techniques that use both spectral and spatial information are more suitable, effective, and robust than those that use only spectral information. The Features employed in this include Morphological profiles, Grey level cooccurence matrix, Discrete Wavelet
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