Abstract
Part I [ Trends Anal. Chem., 11 (1992) 41] focused on the generation of univariate digital images in the chemical laboratory and in industrial situations and on the possible use of operations on univariate images. The concept of a multivariate image was introduced and an example given. This part focuses on the use of multivariate methods to extract problem-dependent, useful information from multivariate images. The example of the powder mixtures given in Part I is further analyzed by principal component analysis. Concepts of exploratory analysis, classification and regression are explained. The use of visual interpretation and statistical diagnostics is emphasized. Ideas about future developments of multivariate image analysis are introduced.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
