Special Section on Image Quality

Content-weighted video quality assessment using a three-component image model

[+] Author Affiliations
Chaofeng Li

Jiangnan University, School of Information Technology, Wuxi, Jiangsu 214122, China

Alan Conrad Bovik

The University of Texas at Austin, Department of Electrical and Computer Engineering, Austin, Texas 78712-1084

J. Electron. Imaging. 19(1), 011003 (January 07, 2010). doi:10.1117/1.3267087
History: Received May 03, 2009; Revised June 23, 2009; Accepted July 21, 2009; Published January 07, 2010
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Objective image and video quality measures play important roles in numerous image and video processing applications. In this work, we propose a new content-weighted method for full-reference (FR) video quality assessment using a three-component image model. Using the idea that different image regions have different perceptual significance relative to quality, we deploy a model that classifies image local regions according to their image gradient properties, then apply variable weights to structural similarity image index (SSIM) [and peak signal-to-noise ratio (PSNR)] scores according to region. A frame-based video quality assessment algorithm is thereby derived. Experimental results on the Video Quality Experts Group (VQEG) FR-TV Phase 1 test dataset show that the proposed algorithm outperforms existing video quality assessment methods.

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Citation

Chaofeng Li and Alan Conrad Bovik
"Content-weighted video quality assessment using a three-component image model", J. Electron. Imaging. 19(1), 011003 (January 07, 2010). ; http://dx.doi.org/10.1117/1.3267087


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