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Journal of Electronic Imaging

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

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.

Paper Details

Date Published: 1 January 2010
PDF: 9 pages
J. Electron. Imag. 19(1) 011003 doi: 10.1117/1.3267087
Published in: Journal of Electronic Imaging Volume 19, Issue 1
Show Author Affiliations
Chaofeng Li, Jiangnan Univ. (China)
Alan Conrad Bovik, The Univ. of Texas at Austin (United States)

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