Import of distortion on saliency applied to image quality assessment

Abstract

There are lots of objective image quality assessment (IQA) algorithms to accurately assess the quality of images recently; however, the characteristics of Human Visual System (HVS) as the ultimate receiver of the visual signal are critical factors affecting IQA. Saliency as a feature reflecting quality has been studied deeply. Since HVS has intricate psychovisual structure and nature, the impact of saliency on IQA algorithms needs still further exploration. This paper focuses mainly on the influence of distortion information on saliency applied on IQA. We eliminated interference of algorithms to study the characteristics of different distortion types and degrees simply. We applied three different objective metrics adding natural scene saliency (NSS) with different adding strategies on the LIVE IQA database. Experimental results demonstrate that the variation in saliency highly depends on the distortion type and degree. IQA algorithms will achieve improving performances on their accuracy by applied proper saliency strategy.