Hi Folks,
My website, Cosgrove's Cosmos, has just published some new posts under its Tips & Techniques Section entitled: "Using Deconvolution In Pixinsight".

https://cosgrovescosmos.com/tips-n-techniques/using-deconvolutioninpixinsight-part1-introduction
This started out to be a simple posting, but it grew so large that I ended up breaking it up into a series of 7 installments to make it easier to parse:
• Part 1 - An Introduction
• Part 2 - An Overview of PFS and Deconvolution
• Part 3 - Workflow Considerations
• Part 4 - Preparing for Deconvolution
• Part 5 - Example - The Draco Triplet
• Part 6 - Example - Messier 63
• Part 7 - Example - Messier 31
Deconvolution in Pixinsight is a very powerful tool for restoring lost detail in an optical system - but it is not the easiest tool to learn to use. When I started, I had a hard time coming up to speed - a problem that is all too common. But with time, I finally learned to use the tool to improve my images.
In this seven-post series, I share seems to work for me, and covers the background of the problem domain so you can understand not just the WHATs and the HOWs - but also the WHYs as well.
Covered are the concepts of Airy Disks and Point Spread Functions, considerations when estimating the PSF model for an image, Workflow considerations, how to create the support images needed by Deconvolution, and how to iterative testing to set needed parameters to get the best results. Finally, I go through three real-world examples using my own images.
I hope you find this helpful. I will be evolving this series in place as I learn more and as I get feedback and suggestions for improvement. ( I will be adding a change log to Part 1 to cover updates).
Thanks for looking!
Pat
My website, Cosgrove's Cosmos, has just published some new posts under its Tips & Techniques Section entitled: "Using Deconvolution In Pixinsight".

https://cosgrovescosmos.com/tips-n-techniques/using-deconvolutioninpixinsight-part1-introduction
This started out to be a simple posting, but it grew so large that I ended up breaking it up into a series of 7 installments to make it easier to parse:
• Part 1 - An Introduction
• Part 2 - An Overview of PFS and Deconvolution
• Part 3 - Workflow Considerations
• Part 4 - Preparing for Deconvolution
• Part 5 - Example - The Draco Triplet
• Part 6 - Example - Messier 63
• Part 7 - Example - Messier 31
Deconvolution in Pixinsight is a very powerful tool for restoring lost detail in an optical system - but it is not the easiest tool to learn to use. When I started, I had a hard time coming up to speed - a problem that is all too common. But with time, I finally learned to use the tool to improve my images.
In this seven-post series, I share seems to work for me, and covers the background of the problem domain so you can understand not just the WHATs and the HOWs - but also the WHYs as well.
Covered are the concepts of Airy Disks and Point Spread Functions, considerations when estimating the PSF model for an image, Workflow considerations, how to create the support images needed by Deconvolution, and how to iterative testing to set needed parameters to get the best results. Finally, I go through three real-world examples using my own images.
I hope you find this helpful. I will be evolving this series in place as I learn more and as I get feedback and suggestions for improvement. ( I will be adding a change log to Part 1 to cover updates).
Thanks for looking!
Pat