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Proceedings Paper

An image similarity measure using enhanced human visual system characteristics
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Paper Abstract

Image similarity measures are crucial for image processing applications which require comparisons to ideal reference images in order to assess performance. The Structural Similarity (SSIM), Gradient Structural Similarity (GSSIM), 4-component SSIM (4-SSIM) and 4-component GSSIM (4-GSSIM) indexes are motivated by the fact that the human visual system is adapted to extract local structural information. In this paper, we propose a new measure which enhances the gradient information used for quality assessment. An analysis of the proposed image similarity measure using the LIVE database of distorted images and their corresponding subjective evaluations of visual quality illustrate the improved performance of the proposed metric.

Paper Details

Date Published: 31 May 2011
PDF: 9 pages
Proc. SPIE 8063, Mobile Multimedia/Image Processing, Security, and Applications 2011, 806310 (31 May 2011); doi: 10.1117/12.883301
Show Author Affiliations
Shahan Nercessian, Tufts Univ. (United States)
Sos S. Agaian, The Univ. of Texas at San Antonio (United States)
Karen A. Panetta, Tufts Univ. (United States)


Published in SPIE Proceedings Vol. 8063:
Mobile Multimedia/Image Processing, Security, and Applications 2011
Sos S. Agaian; Sabah A. Jassim; Yingzi Du, Editor(s)

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