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Is there an easy way (i.e. free or open source tool) to determine the spatial color distribution (i.e "intensity") in a picture or in a region of interest of this picture?

Let's say I used a laser or some lenses and mirrors and a light bulb to adjust a ray of light on a piece of paper in a dark room and photographed the spot and now I want to find out the rough intensity distribution, e.g. if it is a flat distribution or a gaussian or something else.

With what tool is this possible?


migration rejected from Jul 15 '13 at 13:17

This question came from our site for professional, enthusiast and amateur photographers. Votes, comments, and answers are locked due to the question being closed here, but it may be eligible for editing and reopening on the site where it originated.

closed as off-topic by Waffle's Crazy Peanut, Dilaton, BebopButUnsteady, Michael Brown, Manishearth Jul 15 '13 at 13:17

  • This question does not appear to be about physics within the scope defined in the help center.
If this question can be reworded to fit the rules in the help center, please edit the question.

Measuring intensity is not, strictly speaking, photography. It is applied optics, which is a branch of physics. – Michael Clark Jul 13 '13 at 11:49
This question appears to be off-topic because it is about applied physics. – Michael Clark Jul 13 '13 at 12:05
I propose this be moved to StackOverflow. I don't completely understand the question (why is colour distribution == intensity?) but I am certain that such an analysis is trivial in Python or any other language with some image libraries. – Unapiedra Jul 13 '13 at 12:06
Yeah, I was unsure where to post. Because in the end it is about analysing pixels of photographies, I decided for here. If you feel like it, move the question to a better place. – Foo Bar Jul 13 '13 at 12:54
This question appears to be off-topic because it's specifically asking about some kind of tool to calculate some parameter in the picture. We don't encourage such questions... – Waffle's Crazy Peanut Jul 14 '13 at 5:23