How to Select Point Spread Function Empirically for Image Deconvolution?
One way, though not directly visual, is to observe the image statistics.
We have a pretty good idea about the statistics of Natural Images, more specifically, their Gradient Distribution (See Statistics of Natural Images and Models by Jinggang Huang, D. Mumford, What Makes a Good Model of Natural Images by Yair Weiss, William T. Freeman, The Statistic Distribution of Image Gradient - Mathematics StackExchnage and UCLA Stat232A-CS266A Statistical Modeling and Learning in Vision and Cognition - Chapter 2 - Empirical Observations: Image Space and Natural Image Statistics).

So what you can do is see how well the statistics of the result matches the models.
Actually many modern (Prior to the Deep Learning era) Deblurring Methods work according to this approach with very nice results.

Look at Blind Motion Deblurring Using Image Statistics by Anat Levin.