ISSN:
0886-9383
Keywords:
Multivariate images
;
Principal component regression
;
Multivariate image regression
;
Regression model
;
Predicted image(s)
;
Prediction quality scatter plot
;
Visual diagnostic tools
;
Chemistry
;
Analytical Chemistry and Spectroscopy
Source:
Wiley InterScience Backfile Collection 1832-2000
Topics:
Chemistry and Pharmacology
Notes:
Regression between two blocks (usually called ‘dependent’ or Y and ‘independent’ or X) of data is a very important scientific and data-analytical tool. Regression on multivariate images is possible and constitutes a meaningful addition to existing univariate and multivariate techniques of image analysis. The regression can be used as a modeling tool or for prediction. The form of the regression equation chosen is dependent upon problem specification and information at hand. This paper describes the use of principal component regression (PCR). Both model building and prediction are presented for continuous Y-variables. The final goal is to supply new image material that can be used for visual inspection on a screen. Also, visual tools for diagnosis of model and prediction are provided, often based on derived image material. Examples of modeling and prediction are given for six channels in a seven-channel satellite image.
Additional Material:
14 Ill.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1002/cem.1180050206
