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
> 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
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