An Introductory Approach to Spectral Image Analysis Using Machine Learning Classifiers

Machine learning approach in the field of spectral image analysis has achieved remarkable results. Machine learning techniques are the most appealing method for the analysis of spectral pictures because of the high dimensionality of spectral images and the scarcity of annotated data. In this paper, a basic implementation of machine learning classifiers for hyperspectral imaging is presented. It discusses on the preprocessing of hyperspectral images using unsupervised algorithms and performing the classification with supervised ones. This article aims to pique data scientists' curiosity in using cutting-edge machine learning models on their own hyperspectral dataset.