I'm trying to analyze an image obtained by scanning electron microscope(SEM) where different parts of the same image has has different blurring radius. My goal is to determine how blurry different part of this image is.
Clearly, the central part of this image is clear and reveal a lot of details and the upper and down part is rather blurry.
The result of blurring radius needn't be accurate, but needs to show a trend that the central part is not blurry and the further from the central part, the blurrier the image will be.
Is this possible?
Some of my thoughts:
At the beginning I thought about
MaxDetect method given here but later I realized this method may need a image with similar blurring radius everywhere, so this method probably won't work here.
A further goal
What if I would like to know its "approximate blurring radius" instead of just knowing how "blurry" it is?
Goal here is to approximately deternmine the blurring radius r in central part of this image (25%~60% counting from the bottom to the top) where the the object is only "slightly blurred" and still clearly visible.
So how to obtain the blurring radius r within an uncertainty of 30%?
Some other test images: