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Thank you for providing such interesting papers and code for the correction of Fixed Pattern Noise (FPN)! I have a question regarding the applicability of your code to my microscopy dataset.
I am working with grayscale video data recorded from nearly the same view of our microscopy setup for a few seconds. The data includes noise, and I do not have access to clean (noise-free) data for reference. Additionally, my data is not collected from a Multi-View Single-Sensor setup, but I only have several frames from almost the same view.
In your paper, you discuss Single-View Online FPN estimation, but I noticed that this part does not seem to be included in the code.
Given these conditions, I was wondering:
Do you think your code can help remove FPN noise from my data?
If so, could you kindly guide me on which script and settings would be most suitable for my use case?
Your help would be greatly appreciated. Thank you in advance for your guidance!
The text was updated successfully, but these errors were encountered:
Thank you for providing such interesting papers and code for the correction of Fixed Pattern Noise (FPN)! I have a question regarding the applicability of your code to my microscopy dataset.
I am working with grayscale video data recorded from nearly the same view of our microscopy setup for a few seconds. The data includes noise, and I do not have access to clean (noise-free) data for reference. Additionally, my data is not collected from a Multi-View Single-Sensor setup, but I only have several frames from almost the same view.
In your paper, you discuss Single-View Online FPN estimation, but I noticed that this part does not seem to be included in the code.
Given these conditions, I was wondering:
Do you think your code can help remove FPN noise from my data?
If so, could you kindly guide me on which script and settings would be most suitable for my use case?
Your help would be greatly appreciated. Thank you in advance for your guidance!
The text was updated successfully, but these errors were encountered: