The convolver process in imagej has the "normalize kernel" option.
I’m curious about what the normalized kernel does and how it can be implemented in Python to cv2 filter2D.
>Solution :
From the ImageJ docs:
Normalize Kernel causes each coefficient to be divided by the sum of the coefficients, preserving image brightness.
In cv2.filter2D you can pass a kernel, if you want to normalize it (if not already), you just need to divide every entry by the sum of all entries in the kernel.