Have you tried using neat? On Thursday, 10 August 2017 00:04:26 BST Andy wrote: > What you really want is deep nets trained for specific sensors/ISO > combinations > for denoising. Looks like neat doesn't use deep learning (if they would, > I'm sure they'd mention it in their explanation). > So it's unlikely to be state of the art (last time I checked). > > On 07/10/2017 12:05 PM, Tim Rolph wrote: > > Hi, if I have to upscale an image I usually use Reshade from > > www.reshade.com it is a free app the works very well although its only > > for windows but works fine under wine. Oh and its also free. If I ever > > have a problem with noise I use Neat Image https://ni.neatvideo.com/ they > > have a free linux version that is limited to save only in jpg but has > > support for opencl / cuda GPU processing and it gives unbelievably good > > results. > > > > Tim. > > > > On Sunday, 9 July 2017 17:16:12 BST Michael Below wrote: > >> Hi, > >> > >> last week I took a couple of images at a concert, and it turned out > >> that only a small part of each image was interesting. I was too far > >> away, with a wide-angle lens, so the band I wanted to photograph was in > >> a small part in the center of the frame with lots of other stuff around > >> them, stage, audience etc. > >> > >> Now this can be solved by taking better pictures, coming closer, being > >> prepared with a telephoto lens etc. - but there also seems to be a > >> solution that could find its way into darktable. > >> > >> There have been a number of media reports about machine learning > >> experiments by Google etc. to add missing detail to images during > >> upscaling. It seems like the results are often quite convincing. Now I > >> stumbled upon a Github project for this that seems to offer a hands-on > >> solution which might be a basis for implementation in darktable: > >> > >> https://github.com/lucasdupin/ml-image-scaling > >> > >> What do you think? I imagine this would be useful... > >> > >> Cheers > >> Michael > >> _________________________________________________________________________ > >> ___ darktable user mailing list > >> to unsubscribe send a mail to > >> darktable-user+unsubscr...@lists.darktable.org> > > __________________________________________________________________________ > > __ darktable user mailing list > > to unsubscribe send a mail to > > darktable-user+unsubscr...@lists.darktable.org > ____________________________________________________________________________ > darktable user mailing list > to unsubscribe send a mail to darktable-user+unsubscr...@lists.darktable.org
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