Translation insensitive assessment of image quality based on measuring the homogeneIty of correspondence

Image quality assessment plays an important role in the development of many image processing systems. Many full-reference image quality metrics have been proposed and aimed to give the prediction as close as possible to the subjective assessment made by human beings. However, these metrics have a common restriction that pixel-wise correspondence must be established before the evaluation of metric scores. Most of the existing metrics fail to result in accurate prediction even as a test image is differentiated from its original reference merely by one-pixel misalignment. Based on the fact that dissimilar image contents lead to random block correspondence, an image quality assessment method that primarily measures the randomness in the displacement between corresponding blocks from the images in comparison is proposed. The performance of the proposed metric is verified by evaluating the quality of the test images contained in the LIVE and TID2008 databases and the same images translated by various amounts of distance. The correlation between subjective evaluation results and the objective scores evaluated by the proposed metric as well as other five well-know image quality assessment methods is examined. Experimental results indicate that the proposed metric is an effective assessment method that can predict the image quality accurately without the preprocessing of image alignment.