1 January 2010 Content-weighted video quality assessment using a three-component image model
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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.
© (2010) Society of Photo-Optical Instrumentation Engineers (SPIE)
Chaofeng Li, Chaofeng Li, Alan Conrad Bovik, Alan Conrad Bovik, } "Content-weighted video quality assessment using a three-component image model," Journal of Electronic Imaging 19(1), 011003 (1 January 2010). https://doi.org/10.1117/1.3267087 . Submission:


Perceptual tools for quality-aware video networks
Proceedings of SPIE (February 02 2014)

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