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ISSN: 1549-3636 (Print)
ISSN: 1552-6607 (Online)
Research Article Open Access

AN IMPROVEMENT OF STRUCTURAL SIMILARITY INDEX FOR IMAGE QUALITY ASSESSMENT

Emna Chebbi1, Faouzi Benzarti1 and Hamid Amiri1
  • 1 University of Tunis El Manar, Tunisia

Abstract

The image quality assessment has been widely used in image processing. Several researches have been developed and carried considering the Human Visual System (HVS). Under the hypothesis that human visual perception is extremely adapted to retrieve structural information from a scene, the SSIM index is the most widely used in this area, which leads to a better correlation with HVS. Despite its robustness the SSIM presents some limitations in the presence of blur affecting images. In this study, we propose an improved version of the SSIM for blur image assessment. The idea is to combine gradient based SSIM score with that of the structural information of the blur. Experimental results show a good performance.

Journal of Computer Science
Volume 10 No. 2, 2014, 353-360

DOI: https://doi.org/10.3844/jcssp.2014.353.360

Submitted On: 15 August 2013 Published On: 21 November 2013

How to Cite: Chebbi, E., Benzarti, F. & Amiri, H. (2014). AN IMPROVEMENT OF STRUCTURAL SIMILARITY INDEX FOR IMAGE QUALITY ASSESSMENT. Journal of Computer Science, 10(2), 353-360. https://doi.org/10.3844/jcssp.2014.353.360

Open AccessCopyright: © 2014 Emna Chebbi, Faouzi Benzarti and Hamid Amiri. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Image Quality Assessment
  • HVS
  • SSIM
  • GSSIM
  • Blur Estimation