I'm trying to find some information threshold that is required for performing detection of objects in images. However, I'm not sure how exactly to quantify the amount of information contained within an image.
I imagine that looking at the gradients/edges of the image would be a good idea, but simply counting the number of edge pixels doesn't seem enough. Maybe looking for patterns within the edge image?
Perhaps I should look at the image in the frequency domain?
I don't think I can just use Shannon's entropy because it doesn't really "look" at the big picture.
Any help/guidance would be appreciated.
My problem with Shannon's entropy is that it is calculated without considering spatial structures. For example, the following two image have the same entropy score: