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Image quality assessment: Difference between revisions

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** The weights are \(w(i,j) = \sin(\frac{j+0.5}{N}\pi) = \cos(\frac{j+0.5-N/2}{N}\pi)\).
** The weights are \(w(i,j) = \sin(\frac{j+0.5}{N}\pi) = \cos(\frac{j+0.5-N/2}{N}\pi)\).
* Yu ''et al.''<ref name="yu2015framework></ref> propose Spherical PSNR (S-PSNR). In S-PSNR, points are randomly sampled on a sphere and back projected to the reference and reconstructed images. In practice, these randomly sampled points need to be saved for reproducibility. They use 655262 points which are available [https://github.com/mattcyu1/omnieval/blob/master/compsph/sphere_655362.txt on their repo].
* Spherical PSNR (S-PSNR)<ref name="yu2015framework></ref> uses randomly sampled points on a sphere and back projects them to the reference and reconstructed images. In practice, these randomly sampled points need to be saved for reproducibility. They use 655262 points which are available [https://github.com/mattcyu1/omnieval/blob/master/compsph/sphere_655362.txt on their repo].
 
* Spherical Structural Similarity Index (S-SSIM) <ref name="chen2018sssim"></ref> is an extension of SSIM for spherical images.
 
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Samsung has a [https://github.com/Samsung/360tools 360tools] program which can compute WS-PSNR, S_PSNR. However, it requires raw <code>.yuv</code> video.
\begin{align}
\text{S-SSIM}(i, j) &= \frac{2 \mu_x \mu_y + C_1)(2 \sigma_{xy} + C_2)}{(\mu_x^2 + \mu_y^2 + C_1)(\sigma_x^2 \sigma_y^2 + C_2)\\
\text{S-SSIM} &= \frac{\sum_m \sum_n \text{S-SSIM}(m, n) * w(m, n)}{\sum_m \sum_n w(m, n)}
\end{align}
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==Resources==
==Resources==
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<ref name="lee2002foveated">Sanghoon Lee, M.S. Pattichis, A.C. Bovik, (2002) ''Foveated video quality assessment'' IEEE Multimedia 2002.</ref>
<ref name="lee2002foveated">Sanghoon Lee, M.S. Pattichis, A.C. Bovik, (2002) ''Foveated video quality assessment'' IEEE Multimedia 2002.</ref>
<ref name="yu2015framework">Matt Yu, Haricharan Lakshman, Bernd Girod (2015) ''A Framework to Evaluate Omnidirectional Video Coding Schemes'' ISMAR 2015.</ref>
<ref name="yu2015framework">Matt Yu, Haricharan Lakshman, Bernd Girod (2015) ''A Framework to Evaluate Omnidirectional Video Coding Schemes'' ISMAR 2015.</ref>
<ref name="sun2017wspsnr">Yule Sun, Ang Lu, Lu Yu (2017). Weighted-to-Spherically-Uniform Quality Evaluation for Omnidirectional Video. IEEE Signal Processing Letters</ref>
<ref name="chen2018sssim">Sijia Chen, Yingxue Zhang, Yiming Li, Zhenzhong Chen, Zhou Wang (2018). Spherical Structural Similarity Index for Objective Omnidirectional Video Quality Assessment. (ICME 2018)</ref>
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