Abstract
Full reference image quality indices assign a quality
index to a pair of an undistorted reference image and a distorted
image to be assessed; the quality of the index itself is then defined
by its ability to predict the outcome of subjective tests performed
by human observers judging the quality of the same image pair.
In this article, a new DeT based image quality index is introduced
whose complexity is between that of algorithms like SSIM and
complex, HVS-based algorithms like VDP. Detailed experiments
on the LIVE database show that the proposed algorithm performs
best close to or below the visual threshold, and outperforms there
existing algorithms like SSIM or VDP requiring only a mediocre
complexity.
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