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I don't know much about Registax, but I do know a little bit about wavelets in general and the wavelet-based tools in PixInsight, so I can perhaps give you a hint or two...
Wavelet analysis splits an image into a collection of different spatial frequency scales from very fine details up to large scale structures and allows you to perform modifications of the image at each scale. At each scale you can typically remove noise (smooth details) and/or sharpen (which can increase noise). These scales are sometimes called layers, and I think that's the term that Registax uses.
You will probably find that the smallest scale details (first layers) are the most noisy. Sometimes it is a big improvement to heavily denoise or even remove completely the finest scale details. Generally, it's the first few scale levels that you'll want to tweak. Modifying the large scale stuff doesn't usually have positive effects on the image. You need to walk that fine line between removing noise and removing detail.
Hope that helps a little. You will still need to play with the controls and experiment. Images will vary depending on the gear, atmospheric conditions and the object you are imaging. You'll always need to tweak things to see what works best. At least now you might have a better idea of what you're looking at.
Cheers,
Rick.
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