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9 November 2010An image enhancement effect objective assessment method based on visual information fidelity
Assessment of image visual quality is of fundamental importance to numerous image and video processing applications.
Visual information fidelity is a novel criterion that is based on modeling of natural scene statistics, image distortion and
the human visual distortion. Traditionally, image QA algorithms interpret image quality as fidelity or similarity with a
"reference" or "perfect" image. We apply the VIF method on image enhancement effect which takes distorted image as
"reference" image instead of "perfect" image to assess the quality of enhanced image. It provides clear advantages over
the traditional approaches because VIF index is combined with HVS features under certain conditions. In particular, it
can be measured only rely on the original image and enhanced image. We validate the performance of our method with
an extensive subjective study to show that it outperforms current methods in our testing.