Perceptual quality assessment based on visual attention analysis

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Perceptual quality assessment based on visual attention analysis

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International Multimedia Conference archive
Proceedings of the seventeen ACM international conference on Multimedia table of contents

Beijing, China

SESSION: Short papers session 1: content analysis table of contents

Pages 561-564

Year of Publication: 2009

ISBN:978-1-60558-608-3

Authors

Junyong You	Norwegian University of Science and Technology, Trondheim, Norway
Andrew Perkis	Norwegian University of Science and Technology, Trondheim, Norway
Miska M. Hannuksela	Nokia Research Center, Tampere, Finland
Moncef Gabbouj	Tampere University of Technology, Tampere, Finland

Sponsor

SIGMULTIMEDIA: ACM Special Interest Group on Multimedia

Publisher

ACM New York, NY, USA

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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.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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