On the left you will see either "err" or "fit". "err" is the raw score of the metric. "fit" is the metric after fitting to a 0-10 human visual quality scale. SSIM err is actually percent acos angle as usual.
The fit score is 0-10 for 0 = complete ass and 10 = perfect, but I have set the graph range to 3-8 , because that is the domain we normally care about. 8 = very hard to tell the difference.
x264 on mysoup , testing different "tune" options. I'm using my y4m to do the color convert for them which helps a lot.
Well "tune psnr" is in fact best on psnr - you can see a big difference on the RMSE chart. "tune ssim" doesn't seem to actually help much on SSIM, it only beats "tune psnr" at very low bit rate. "tune stillimage" just seems to be broken in my build of x264.
Oh, and I use "xx" to refer to x264 because I can't have numbers in the names of things.
Henceforth we will use tune = ssim. (change : psnr)
ADDENDUM :
I looked into this a little more on another image (also trying x264 with no explicit tune specified) :
You can see that "--tune ssim" does help a tiny bit on MS-SSIM , but it *hurts* IW-MS-SSIM , which is a better metric (it hurts also on MyDctDeltaNew). Though the differences are pretty negligible for our level of study. No explicit tune x264 is much worse. "tune psnr" seems to be the best option according to our best metrics.
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