Noise Reduction Techniques


I've been thinking about noise reduction techniques the past few days and have been trying to find the most efficient noise reduction method. 

I process all my images using Pixinsight and Photoshop, and I think they both offer some excellent noise reduction techniques. 

Here are some of my favourites: 


TGV denoise - I find that this works well for background noise reduction and noise reduction on the target itself but I've noticed that there are some artefacts caused by TGV denoise. These are usually relatively easy to get rid of using the MLT tool but harder to remove on the nebulosity, so I tend to only use TGV denoise to denoise the background of my images and not the target itself.

MLT (Multiscale Linear Transform) - As I mentioned before, this tool is great for smoothing out the background of an image and removing larger noise artifacts.

EZ Denoise - I find EZ Denoise to be surprisingly effective, even when using just the default settings! I do find that it can sometimes over do it but I find that blending a mixture of the original image and the EZ Denoised one using Pixelmath helps you to get a good balance. The only downside is it takes SO LONG! But I guess the end result is worth it.

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Camera Raw Filter -> Details -> Noise Reduction - This is a great and easy way to reduce noise in your astrophotos. The only issue I have with it is that it tends to leave some strange artifacts on certain areas and, when overused, it can make your image look a bit unrealistic.

Gaussian Blur - This is an awesome trick I learned that can help alot with color noise reduction. Create a new layer and set its mode to "color" then apply a slight gaussian blur to the layer. I find this very effective with little negative impact to the image. However, if you over blur the layer, you will lose some color and color details so I wouldn't blur the image more than a few pixels.

Those are the methods I use - Let me know what noise reduction methods you use and which methods you think are the most effective in the comments!

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