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