Hyperspectral Imagery Classification Using Deep Learning

Abstract

Hyperspectral Imagery (HSI) data analysis and processing is an emerging topic in the arena of remote sensing and earth observation technology. Recently land cover deep learning based classification algorithms have become an emerging research area and these techniques are used in majority of applications like agriculture, military surveillance, environmental analysis, urban investigation, mineral exploration. An end-to-end deep learning architecture is introduced in this paper which extracts band from spatial-spectral features and also performs classification with comparative classifier analysis and provides state-of-the-art efficiency.