Open matejak opened 9 years ago
Any thoughs on how to improve the performance? I've having trouble with high resolution microscope images with quite a lot of overlap. See this notebook: http://nbviewer.ipython.org/github/arve0/master/blob/master/image%20registration%20precision.ipynb
I have took a look at your data. You are right that performance was not my concern - I wanted to get a prototype running that can be improved. Anyway, the main facts about your data are those:
Therefore, you can use the tiling functionality that is part of the ird
utility in the following way:
ird undersampled1.png cut2.png --tile --show --print-result
and watch the result. You should get relative shift between the 1st undersampled image and the cut from the 2nd image. I have tried that, it seems to work. Since you know the origin of the cut, you can compute the total shift by adding those two up.I can't assist you very much since I am now in the final phase of writing thesis. The tiling functionality is not part of the Python API yet, but it is probably in a good enough shape for your needs. Look at cli.py:435
and the documentation part that mentions tiling.
Thanks for the swift response! Heh, almost same situation here, trying to finish my (master) thesis.
I'll try using a cut, thanks again.
There is an idea in the air - calculate std. dev. from the CPS "background" and compare it to the peak value.
Evaluation of phase correlation success is flaky ATM