A study on using spectral saliency detection approaches for image quality assessment

Recent developments in the field of full reference image quality assessment (FR-IQA) have witnessed the use of spectral residual (SR) based index as a fast measure with high accuracy. Following SR, several variants of spectral measures for visual saliency have come up. These new measures differ in their computational times as well as in performances and have established themselves better than or competitive with SR as measures of visual saliency. The effectiveness of these measures in FR-IQA is still an open question. In this paper, a study to evaluate the performance of the recent spectral approaches for visual saliency (hence spectral saliency) for FR-IQA is presented. We have fixed a framework for FR-IQA to maintain uniformity in the evaluation process. Also, the parameters required by the framework are chosen to bring out the best potential of each measure. Our experiments on six benchmark databases reveal some insightful details about the usage of these measures to form an FR-IQA measure.