![]() ![]() It’s very rarely that I can hold a camera steady enough at 1/15s that lens sharpness will actually improve the image, so I’m not gaining resolution by using it. Again, DeepPRIME does a much better job.Īs a side note, I have found that turning off lens sharpness for high ISO cases helps with noise reduction. Also, as in some of Peter’s examples above, Prime sometimes would create ghosts around small bright areas like lights. Prime was not managing, but DeepPRIME does a much better job. The resulting noise levels are bad - the corners particularly so because of lens correction and vignetting. I have some night shots at high ISO that were also deliberately unrexposed by about 2EV. PRIME does well in most instances, but DeepPRIME does a better job on hard cases. Useful at times, and it would be welcome addition to Topaz Denoise as well to cut down on the number of applications one must use.I’ll add my vote for DeepPRIME being a great step forward. Topaz Sharpen and DXO allow adding back some texture by introducing Film Grain. Hopefully Topaz will fix that in the upcoming updates. Even Photoshop workflow with Topaz is not as good. This is something DXO does far better job off. Than Topaz leaves ugly blotches of color everywhere and moving color noise slider only destaurates colors in the image, indiscriminately. The biggest problem I think with Topaz De noise algorithms is the high degree of color noise when you push camera sensors to the max. By combining the two, its possible to get quite good results even in challenging situations. And than AI clear mode for the parts the Low Light destroyed. The workaround would be to use two models from de noise and than layer the results and mask it out in Photoshop.įor example using Low Light mode for everything not with fine details like text in the image. Yes, I think most Topaz models try to invent details while some other AI programs like DXO tries to not invent just clean up. “What is particularly noticeable are of course the colors, where Denoise has problems, and details like fonts.” Where one can compare the two tools is features and workflow advantages and limitations. Results will vary and its not about which tool but results on the end. Depending on the skill of the user, particular image etc. But if you have supported RAW files DXO deep prime + Topaz Sharpen, not de noise produces by far the best overall results. Topaz is only option, DXO is not even available. Which means that if you are Fuji shooter or working on unsupported RAW file sor just scanned files etc. Where Topaz can do no wrong.Īnother benefit of Topaz is that works with JPEG or TIFF’s and not only supported RAW files like DXO. This leads to confirmation bias, quite present among few people on this forum. Doing a random set and forget comparison like this on a random file will produce all kinds of results and one can choose to use which ever one thinks they like better as a software. In other words its the combination or tools and workflow that produces best results. ![]() However, the best workflow I found is DXO for everything regarding RAW conversion, including de noising, and than applying sharpening to TIFF or JPEG using Sharpen AI from Topaz. ![]() Secondly, build into the De-noise from topaz are sliders for sharpening etc. So this means you have to use Topaz de noise at the end on a TIFF or JPEG, adding extra step, and limiting some of the features like shadow recovery. There is no correction of lens distortions and color rendition is something one cannot adjust and when you export DNG file its not fully readable as original RAW by other programs. Speaking of RAW de noising, its another problem since Topaz is not really designed for it. to some Extent this can be mitigated by first applying color noise removal in programs such as Lightroom or Capture one and than applying only luminance noise reduction in Topaz, but at the expense of not being able to apply the de noising in RAW. This is where DeepPrime does amazing job and topaz does not. For example, Topaz has serious problems with lot of color noise when camera sensor is stretched to the limit. The user input and ability to adjust is the critical component and this is where most of these types of tests fail, because they don’t rely much on ability to adjust the image by skilled user.Īlso every image is going to be context sensitive. This is like testing colors rendition in RAW files. I think you guys are doing flawed comparisons. ![]()
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