Last we use selected functions (such as Harris statistical approach) to calculate measurements with SCM and do feature extraction and classification.
For tradition feature extraction, approaches are usually categorized into structural, statistical, model based and transform.
SCM based on discrete wavelet frame transformation make use of both correlations and feature information so that it combines structural and statistical benefits.
In order to do SCM we have to use discrete wavelet frame (DWF) transformation first to get a series of sub images.
The decomposition is then continued in the LL channels only as in the wavelet transform, but since the image is not subsampled, the filter has to be upsampled by inserting zeros in between its coefficients.