If you have a low SNR then it affects all processing. Again, I'm not claiming anything. I'm just thinking out loud what could cause linearfit to clip your data like that. I tried to play with the rejection scales of it and it helps a bit. dnalinearfit is more robust and gave good fit easily.
If you have an image scale of 1.4"/px then that is pretty good already. Drizzle really helps when you are undersampled. When you are properly sampled to your seeing then drizzle does not change much. When you are oversampled it will hurt you.
Think about it in the simplest way (in reality of course its not), you take the light from a single pixel and spread it over 4. Yes the algorithm is sophisticated and does magic. No argue about that. But you cannot bypass basic concepts. If you are undersampled then there is "hidden" resolution to be recovered. If you are oversampled then you're just lowering your SNR really without getting more details.
That is how I see things. In a simple way. Its more complicated than that. I'm sure others will have opinions about this as well.
By the way, you do not need to drizzle x2 and then downsample x2 to get the effect you're getting with noise reduction. You could just drizzle x1 (yes I know that I wrote x1) and you are going to get the same effect. Its an interpolation algorithm and will do a noise rejection techniques when manipulating the data.
The best noise reduction technique is... take more data.
Edited by imtl, 07 July 2020 - 02:52 AM.