zvrastil
Well-known member
Juan Conejero said:I recommend trying wavelet-based noise reduction in the first place for deep sky images.
Maybe, it's good idea to add ATWT to NoiseReduction category then...
Juan Conejero said:I recommend trying wavelet-based noise reduction in the first place for deep sky images.
I started to use this NR tool after you first presented it to us (with release 1.5).
Juan Conejero said:Now the image is no nice and seems to respond so well to everything I do, that I can't resist doing a more elaborate example. This is a first nonlinear stretch. As is customary in PixInsight, we have high precision tools so this can be done perfectly in a single step --forget all that ugly multiple stretches so common in other applications. They simply reflect the inability of those applications to handle real image data (they are image retouching toys, not real image processing software).
- Wavelet-based noise reduction works on a per-layer basis. By applying noise reduction to the first wavelet layer, we can suppress or reduce high-frequency noise. On subsequent layers we can apply noise reduction to larger structures. In this case we have worked on the first four wavelet layers, that is up to the scale of eight pixels.
- Wavelet noise reduction parameters are very easy to understand. This is one of the reasons why wavelet-based noise reduction can be so powerful. We have the following parameters for each layer:
Hello @Juan Conejero
it seems strange to me that I can not handle this in a more efficient way but I don't know if I should try different parameters of differents process or anything else ...
Hello @ngc1535
From your perspective, what would you do for this "granularity" of the backgroun chrominance noise ?
Thanks again for your time
You did not mention or take into account the difference in debayer method as a correlating factor in the noise you are concerned about.
VNG has an interpolation that cross-correlates across many pixels at larger scales.
You might consider to continue your analysis by simply extracting pixels via the 'superpixel' method.