Perceptual quality assessment based on visual attention analysis

Authors:
Junyong You;Andrew Perkis;Miska M. Hannuksela;Moncef Gabbouj
Affiliations:
Norwegian University of Science and Technology, Trondheim, Norway;Norwegian University of Science and Technology, Trondheim, Norway;Nokia Research Center, Tampere, Finland;Tampere University of Technology, Tampere, Finland
Venue:
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Year:
2009

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Abstract

Most existing quality metrics do not take the human attention analysis into account. Attention to particular objects or regions is an important attribute of human vision and perception system in measuring perceived image and video qualities. This paper presents an approach for extracting visual attention regions based on a combination of a bottom-up saliency model and semantic image analysis. The use of PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural SIMilarity) in extracted attention regions is analyzed for image/video quality assessment, and a novel quality metric is proposed which can exploit the attributes of visual attention information adequately. The experimental results with respect to the subjective measurement demonstrate that the proposed metric outperforms the current methods.