Hi Stuart
You are right that the Moffat reference is to the mathematical function used to model the star shape. The number following the "Moffat" designation refers to one of the parameters (beta) of the Moffat function. If you know the beta parameter that best matches the stars in your image then you can select the appropriate function. If not, as you have, select the "Moffat" choice and the script will try to find the best beta, along with the other Moffat parameters, to match your stars.
The more "blocky" the generated psf the smaller the number of pixels over which your stars are spread. Deconvolution works best on images where the stars are well or over sampled, ie they cover several pixels - these are the images on which deconvolution will have greatest beneficial effect.
This document details the DynamicPSF process available in PixInsight. It has some very helpful information on PSFs.
CS, Mike
You are right that the Moffat reference is to the mathematical function used to model the star shape. The number following the "Moffat" designation refers to one of the parameters (beta) of the Moffat function. If you know the beta parameter that best matches the stars in your image then you can select the appropriate function. If not, as you have, select the "Moffat" choice and the script will try to find the best beta, along with the other Moffat parameters, to match your stars.
The more "blocky" the generated psf the smaller the number of pixels over which your stars are spread. Deconvolution works best on images where the stars are well or over sampled, ie they cover several pixels - these are the images on which deconvolution will have greatest beneficial effect.
This document details the DynamicPSF process available in PixInsight. It has some very helpful information on PSFs.
CS, Mike