What are method of Reduce Reference Quality Metric? I have trouble to find the fit method....

This is an article from paper:

"Reduced-reference (RR) image quality assessment

metrics (IQA) evaluate the quality of images by extracting a

parameter set from the original reference image and using

this set in place of the actual reference image. In this paper,

we propose a novel RR-IQA metric based on Contourlet

transform. By combining Contourlet transform with a

version of the hidden Markov model--Gaussian scale

mixtures (GSM), the marginal distributions of neighbor

coefficients in the Contourlet domain are modeled. With

Contourlet transform as a pre-processing, the marginal

histogram of coefficients in each subband can be well fitted

by Guassian distribution after divisive normalization

transforming. The standard derivation of the fitted

Guassian transform and fitted error will be extracted as

feature parameters. Experiments show that the proposed

metric has good consistency with human subjective

perception."

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My goal: I wanna perform that new images are same with references images by state similarity of identified foreground. I attached those images.

*new image (NewImage) that I want to referenced from reference image (ReferenceImage) and stated that both of them have similarity cause of foreground area

*Reference Image is standard dataset and wanna perform this and stated that if new images have same area foreground then the new image has good quality