Hyperspectral image analysis. A tutorial

This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares – Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. [Display omitted] •Comprehensive tutorial of Hyperspectral Image analysis.•Hierarchical discrimination of six classes of plastics containing flame retardant.•Step by step guidelines to perform class-modeling on hyperspectral images.•Fusion of multivariate data analysis and digital image processing methods.•Promising methodology for real-time detection of plastics containing flame retardant.