jimh12345 Posted October 9 Share Posted October 9 I have some recent night photos that would be good, except for noisy skies due to low light. It's hard to avoid. Standard noise reduction can reduce such noise, but never really get rid of it. What it seems to do is eliminate fine-grained noise at a cost of creating larger scale artifacts, and banding, in their place; you can never really get that sky smooth. Photographers fight with this endlessly. Thinking about this, it seems what I want is a tool that would identify all these adjacent pixels of similar levels and dark blue colors, and replace them all with pixels of ONE level and color, based on averaging. In other words, homogenize that sky. And it seems to me this should be possible. Does anyone know of a way to do this? Quote Link to comment Share on other sites More sharing options...
Ldina Posted October 9 Share Posted October 9 @jimh12345 check out affinity help, Stacking multiple images to average out and reduce noise. There are quite a few tutorials on YouTube showing how to do this. You’ll need multiple exposures to do this, of course. James Ritson has a tutorial on this somewhere but I couldn’t find it. It might be a legacy tutorial from version 1. It may not help if you have just a single exposure, but if you do a lot of this, you can plan it in the future. You may also be able to find some AI solutions that work. Quote 2017 15" MacBook Pro, 16 GB RAM, Ventura v13.7, Affinity Photo/Designer/Publisher v1 & v2, Adobe CS6 Extended, LightRoom v6, Blender, InkScape, Dell 30" Monitor, Canon PRO-100 Printer, i1 Spectrophotometer, i1Publish Link to comment Share on other sites More sharing options...
jimh12345 Posted October 9 Author Share Posted October 9 @Ldina, I'm familiar with some of those tricks. In this case I have only single exposures and was thinking there should be a simpler way to "average" an area like a noisy sky. Let's say there was an "averaging" tool - you'd set boundary values for color and luminance, then brush over an area to average it. Anything not within those parameters would be ignored. Quote Link to comment Share on other sites More sharing options...
GaryLearnTech Posted October 9 Share Posted October 9 @jimh12345 I was looking at the Help pages for details about some of the different Blur filters a few days ago for something I've been tinkering with. I wonder if careful area selection and then application of either the Bilateral Blur or the Maximum Blur might help with your individual night photos? Quote —— Gary —— Photo/Designer/Publisher: Affinity Store, v2.5.n release (and, since I have the space, the last v1 versions too). Mac mini (M1, 2020), 16GB/2TB, macOS Sonoma iPad Pro (M4) 13", 1TB, Apple Pencil Pro, iPadOS 17.6.1 MacBook Pro (Intel), macOS Sonoma Windows 10 via VMware Fusion Link to comment Share on other sites More sharing options...
smadell Posted October 9 Share Posted October 9 How about this? Select the sky (that is, omit land, vegetation, etc). Duplicate to a new pixel layer. Apply a Compound mask that intersects luminosity (everything except the brightest areas, like stars) and hue (looking for only blues similar to the sky). Apply an Average Blur (from the Filter menu) to the pixel layer. Adjust opacity and/or blend mode (darker color?) to fine tune the result. I’m not at my computer and this is all very off-the-cuff, but it seems like it might work. Quote Affinity Photo 2, Affinity Publisher 2, Affinity Designer 2 (latest retail versions) - desktop & iPad Culling - FastRawViewer; Raw Developer - Capture One Pro; Asset Management - Photo Supreme Mac Studio with M2 Max (2023); 64 GB RAM; macOS 13 (Ventura); Mac Studio Display - iPad Air 4th Gen; iPadOS 18 Link to comment Share on other sites More sharing options...
jimh12345 Posted October 10 Author Share Posted October 10 @GaryLearnTech, what I want to avoid is the "careful area selection" part. @smadell - interesting, I'll have to find out what a "compound mask" is. Quote Link to comment Share on other sites More sharing options...
Ldina Posted October 10 Share Posted October 10 @jimh12345 Here's one approach, or try a variation using different blend modes, etc. This image was shot at ISO 1600 in an extreme contrast setting, so the dark areas are super underexposed and very noisy. 1. First, I'd do some noise reduction in the Develop Persona if you are shooting RAW. Might as well remove some noise to stack the deck in your favor. 2. Below, I duplicated this image twice (Merge Visible). I set the layer blend mode to Darker Color, but you can try other darken modes as well, Average, etc. 3. I selected the Move Tool and used the left, right, up and down arrow keys to slightly mis-register the duplicate images. There was a different placement of each of the duplicates. This is 'sort of' a poor man's stacking behavior, trying to misregister the noise in the darker parts of the image to make it less visible.. 4.. Finally, I used Blend Ranges to limit the effect to the darkest tones where the noise is the worst. Most of the resulting image will be unaffected, due to the chosen blend range. Only the dark areas (under about 10-20%) will be affected, which does result in some mistregistration, but those tones are mostly close to black anyway, so clarity and detail were of less concern, but noise was the biggest issue. Worth a try. Quote 2017 15" MacBook Pro, 16 GB RAM, Ventura v13.7, Affinity Photo/Designer/Publisher v1 & v2, Adobe CS6 Extended, LightRoom v6, Blender, InkScape, Dell 30" Monitor, Canon PRO-100 Printer, i1 Spectrophotometer, i1Publish Link to comment Share on other sites More sharing options...
jimh12345 Posted October 10 Author Share Posted October 10 @Ldina, an interesting and creative approach which I will need to try. I can tell you one thing, though. I've been using Capture One for years. But I just tried DxO Photolab 8, and with its noise reduction, my noise problems with this image are GONE. It's much more powerful than Capture One, with the tradeoff being that its noise reduction can only be applied globally. Some fine detail is lost, but nothing that matters for this image. So maybe we all just wait for better noise reduction software to become ubiquitous? Quote Link to comment Share on other sites More sharing options...
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