Multivariate image analysis in the process industries: A review

This paper provides an overview of the history, methods and applications of multivariate image analysis methods as developed for use in the process industries. It presents a general framework for the methods and their applications and discusses them under image analysis methods that use only spectral features of the images, such as Multivariate Image Analysis (MIA), and Multivariate Image Regression (MIR), and those that use textural features and combinations of textural and spectral features. The emphasis is on applications such as monitoring, prediction and control, and on those aspects of the methods that make them suitable for these tasks.