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Fast structural similarity index algorithm

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Abstract

The development of real-time image and video quality assessment algorithms is an important direction on which little research has focused. Towards this end, we present a design of real-time implementable full-reference image/video quality algorithms that are based on the Structural SIMilarity (SSIM) index and multi-scale SSIM (MS-SSIM) index. The proposed algorithms, which modify SSIM/MS-SSIM to achieve speed of execution, were tested on the LIVE Image Quality Database and LIVE Video Quality Database. The experimental results show that the performance of the new, fast algorithms is commensurate with that of SSIM and MS-SSIM, but with much lower computational complexity. Indeed, the proposed Fast MS-SSIM algorithm is 10 times faster (lower complexity) than the MS-SSIM algorithm, while the proposed Fast SSIM is 2.68 times faster than SSIM without parallel computing optimization.

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Notes

  1. An accurate truncated expansion approximation learned by author ACB whilst lecturing at Texas Instruments in the 1990s.

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Authors and Affiliations

  1. Laboratory for Image and Video Engineering (LIVE), The University of Texas, Austin, USA

    Ming-Jun Chen & Alan C. Bovik

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  1. Ming-Jun Chen
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  2. Alan C. Bovik
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Correspondence to Ming-Jun Chen.

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Chen, MJ., Bovik, A.C. Fast structural similarity index algorithm. J Real-Time Image Proc 6, 281–287 (2011). https://doi.org/10.1007/s11554-010-0170-9

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  • DOI: https://doi.org/10.1007/s11554-010-0170-9

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