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I agree that neural networks work wonders with noise, but I'd add - it all depends on the original state of the photo. If the shot is really dark or blurry, even a neural network won't pull out a decent result. Personally, for dogs I often use Topaz Gigapixel AI and regular Lightroom - the first one is great for details, the second quickly removes noise without losing sharpness. The main thing is not to overdo it, otherwise the photo ends up looking plastic.
You can improve it, but you gotta understand the limits. I run into this problem all the time myself, when I'm photographing mushrooms in the forest with bad lighting on an old camera. The main tool is neural network software for noise reduction. In my opinion, Topaz Gigapixel AI and DxO PureRaw work best (paid), though they're expensive. For hobbyists there are free options like ON1 Photo Raw Free or even built-in filters in Adobe Lightroom Classic. Important thing: I always check the result myself, because algorithms sometimes blur fine details while removing noise. So you need to experiment with the strength of the processing.
If the noise is absolutely killing the image, then besides noise reduction you should use sharpness and contrast to get the clarity back. But honestly: if the original photo was shot at maximum ISO and is really dark, then don't expect miracles. Neural networks work well on moderately noisy photos with relatively recognizable details. I'd recommend trying a few programs on trial versions first to see if it'll actually help in your case. By 2026 the noise processing technology is already pretty good, but it's not magic.
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