RobCoeff

Robust estimation of subspace coefficients

This package contains Matlab functions, which perform robust estimation of subspace coefficients in PCA, CCA and LDA methods. It contains the following files (Matlab functions):

• PCA Principal Component Analysis. Creates the principal subspace.
• IS2FS Maps images from image space to feature space.
• FS2IS Maps vectors of subspace coefficients from feature space to image space.
• IS2FSROB Maps vectors of subspace coefficients from feature space to image space in a robust manner.
• CCA Canonical Correlation Analysis. Computes canonical correlation vectors.
• CCAAPCA CCA-after-PCA. Calculates CCA of augmented PCA coefficient vectors.
• LDA Linear Discriminant Analysis. Computes LDA eigenvectors.
• LDAAPCA LDA-after-PCA. Calculates LDA of augmented PCA coefficient vectors.
• DISPIMGS Displays images.
• DEMOPCA Demo of robust estimation of principal components.
• DEMOCCA Demo of robust estimation of canonical correlation coefficients.