Date: | March 31, 2016 |
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Location: | DC 1331 |
Time: | 11:30 |
Chair: | Omar Zarifi |
Date: | April 7, 2016 | April 14, 2016 | April 21, 2016 | April 28, 2016 |
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Location: | DC 1331 11:30 | DC 1331 11:30 | DC 1331 11:30 | DC 1331 11:30 |
Chair: | Dan Vogel |
Christopher Batty |
Bill Cowan |
Ryan Goldade |
Technical Presentation: | Omar Zarifi |
Christopher Batty |
Dan Vogel |
Bill Cowan |
Andrew Tinits |
Title : The Structural Similarity Index
Abstract: The Structural SIMilarity (SSIM) index is a method for measuring the similarity of two images. It can be viewed as a quality measure of one of the images, provided the other image is regarded as of perfect quality. SSIM is designed to improve on traditional methods such as peak signal-to-noise ratio (PSNR) and mean squared error (MSE), which have proven to be inconsistent with human visual perception. The first version of SSIM, called the Universal Quality Index (UQI), or Wang-Bovik index, was developed by Zhou Wang (now at the University of Waterloo) and Al Bovik in 2001. It was modified into the current version of SSIM in a 2004 paper entitled "Image quality assessment: From error visibility to structural similarity”. The 2004 SSIM paper has been cited more than 10,000 times, making it among the highest cited papers in the image processing field. It was accorded the IEEE Signal Processing Society Best Paper Award in 2009, and the inventors of SSIM were each accorded an individual Primetime Engineering Emmy Award in 2015. |
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