Journal of Applied Mathematics

  • J. Appl. Math.
  • Volume 2014, Special Issue (2014), Article ID 294870, 10 pages.

Total Variation Based Perceptual Image Quality Assessment Modeling

Yadong Wu, Hongying Zhang, and Ran Duan

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Visual quality measure is one of the fundamental and important issues to numerous applications of image and video processing. In this paper, based on the assumption that human visual system is sensitive to image structures (edges) and image local luminance (light stimulation), we propose a new perceptual image quality assessment (PIQA) measure based on total variation (TV) model (TVPIQA) in spatial domain. The proposed measure compares TVs between a distorted image and its reference image to represent the loss of image structural information. Because of the good performance of TV model in describing edges, the proposed TVPIQA measure can illustrate image structure information very well. In addition, the energy of enclosed regions in a difference image between the reference image and its distorted image is used to measure the missing luminance information which is sensitive to human visual system. Finally, we validate the performance of TVPIQA measure with Cornell-A57, IVC, TID2008, and CSIQ databases and show that TVPIQA measure outperforms recent state-of-the-art image quality assessment measures.

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J. Appl. Math., Volume 2014, Special Issue (2014), Article ID 294870, 10 pages.

First available in Project Euclid: 1 October 2014

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Wu, Yadong; Zhang, Hongying; Duan, Ran. Total Variation Based Perceptual Image Quality Assessment Modeling. J. Appl. Math. 2014, Special Issue (2014), Article ID 294870, 10 pages. doi:10.1155/2014/294870.

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