Varimax extended rotation applied to multivariate spectroscopic image analysis

摘要

A new approach for spectral image analysis called the Varimax extended rotation (VER) has been developed. VER employs a four-step procedure to resolve image data. In the first step, the data are pretreated to ensure they are is in a form suitable for principal component analysis. The second step involves reducing the dimensionality of the data using principal component analysis. In the third step, the significant principal components are rotated to identify single component regions in the spectral image. The fourth step uses alternating least squares (ALS) to improve the estimates of the spectral profiles of each component. Results from simulated and real Raman imaging data of water in oil emulsions demonstrate the efficacy and efficiency of the proposed method. (C) 2003 Elsevier B.V. All rights reserved.