Objective image quality assessment (IQA) is imperative in the current multimedia-intensive\nworld, in order to assess the visual quality of an image at close to a human level of ability.\nMany parameters such as color intensity, structure, sharpness, contrast, presence of an object, etc.,\ndraw human attention to an image. Psychological vision research suggests that human vision is\nbiased to the center area of an image and display screen. As a result, if the center part contains\nany visually salient information, it draws human attention even more and any distortion in that\npart will be better perceived than other parts. To the best of our knowledge, previous IQA methods\nhave not considered this fact. In this paper, we propose a full reference image quality assessment\n(FR-IQA) approach using visual saliency and contrast; however, we give extra attention to the center\nby increasing the sensitivity of the similarity maps in that region. We evaluated our method on three\nlarge-scale popular benchmark databases used by most of the current IQA researchers (TID2008,\nCSIQ and LIVE), having a total of 3345 distorted images with 28 different kinds of distortions.\nOur method is compared with 13 state-of-the-art approaches. This comparison reveals the stronger\ncorrelation of our method with human-evaluated values. The prediction-of-quality score is consistent\nfor distortion specific as well as distortion independent cases. Moreover, faster processing makes it\napplicable to any real-time application.
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