I want to try CliJ for deconvolving some images for a client, but the plugin asks for a convolution kernel. How do I develop a convolution kernel? Can I use a PSF image? The image was taken with a 10X objective with a 0.45 NA. Thank you.
But thanks for trying. Would you mind letting us know how it goes?
The deconvolution with CliJ went nowhere - I got a completely blank image. I have attached the image I want to deconvolve and a 2D PSF image I generated with the plugin PSF Generator with Born & Wolf Optical Model. I would appreciate whatever advice you have to offer. Thank you!
sorry for the inconvenience. I tried with your images and can confirm the black result image. Obviously there is a bug in CLIJs deconvolution. However, if you convert your image to 32-bit before processing it, it should work. I will fix this bug with the next release. Thanks for reporting the bug btw! I feedback
Furthermore, your PSF image is huge (256x256 pixels) and doesn’t contain much. You can crop out a center part, e.g. 33x33 pixels around the bright spot to speed up deconvolution.
By converting your input image to 32-bit and cropping the PSF to 33x33, I get this result after 10 iterations on my Intel GPU within just some seconds:
Could you please try again and let me know if it works?
Ah, I noticed that my PSF image was 32-bit while my Hoescht image was 16-bit. So having different bit depths doesn’t work for CliJ deconvolution? Converting my image to 32-bit did the trick. CliJ deconvolution worked pretty darn well! It pulled out edges very nicely in the very dense, central region of nuclei. Thanks a million!
It’s supposed to work with different bit depths. And it will work with the next release. Thanks again for trying and reporting the bug. You made CLIJ better today!