4 ms·
Hm, any examples of that? I found https://dl.acm.org/doi/10.1145/2766891 https://dl.acm.org/doi/10.1145/2766891 but I don't like the comparisons. Any designer
by anotheryou 4y ago
Hm, any examples of that?
I found https://dl.acm.org/doi/10.1145/2766891 https://dl.acm.org/doi/10.1145/2766891 but I don't like the comparisons. Any designer will tell you, after down-scaling you do a minimal sharpening pass. The "perceptual downscaling" looks slightly over-sharpened to me.
I'd love to compare something I sharpened in photoshop with these results.
- brucethemoose2 4y agoThat implementation is pretty easy to run! The whole Python block (along with some imports) is something like: clip = core.imwri.Read(img) clip = muf.ssim_downscale(clip, x, y) clip = core.imwri.Write(clip, imgoutput) clip.set_output() > Any designer will tell you, after down-scaling you do a minimal sharpening pass This is probably wisdom from bicubic scaling, but you usually dont need further sharpening if you use a "sharp" filter like Mitchell. Anyway I havent run butteraugli or ssim metrics vs other scalers, I just subjectively observed that ssim_downscale was preserving some edges in video frames that Spline36, Mitchell, and Bicubic were not preserving.