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

Chaofeng Li; Alan Conrad Bovik

doi:10.1117/1.3267087

1 January 2010 Content-weighted video quality assessment using a three-component image model

Chaofeng Li, Alan Conrad Bovik

Author Affiliations +

Journal of Electronic Imaging, Vol. 19, Issue 1, 011003 (January 2010). https://doi.org/10.1117/1.3267087

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.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Chaofeng Li and 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

Published: 1 January 2010

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