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2009
ACM

Perceptual quality assessment based on visual attention analysis

10 years 10 months ago
Perceptual quality assessment based on visual attention analysis
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. Categories and Subject Descriptors I.4.10 [IMAGE PROCESSING AND COMPUTER VISION]: Image Representation General Terms: Algorithms, measurement
Junyong You, Andrew Perkis, Miska M. Hannuksela, M
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2009
Where MM
Authors Junyong You, Andrew Perkis, Miska M. Hannuksela, Moncef Gabbouj
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