Determining the smaller step size would be frustrating for some because of its sensitivity (another thing to train). This value would ideally be the minimum number of steps to produce a meaningful change in HFR. Unfortunately, HFR will vary even without moving the focuser due to camera SNR and environment. Definitely something to think about...
Understood regarding ROI.
Users who are accustomed to using a Bahtinov mask likely know their (fine step). The logic can repeat the process 2-3 times and pick the average result to help filter SNR and environment.
I believe the benefits of this "SuperFocus" feedback loop are...
- It's relatively immune to scope focus backlash and other hysteresis issues.
- The "closed loop" feedback is more robust and repeatable than the "open-loop" curve fitting.
- It has significant room for future enhancements. Examples...
a. Dynamic optimization for (fine step) through observation of the current and prior HFR.
b. Real-time graphic display of star focus for optional manual intervention.
c. Potential for transparent continuous focus with little or no effect on guiding due to the small (fine step).
d. Ability to warn the user when HFR is creeping up.
Just my 2-cents.