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+--- Thread: Maximas in grayscale image (/thread-28996.html)
Maximas in grayscale image - yliats - Aug-13-2020
I have a grayscale image (2d matrix), and I want to extract N (defined integer) maximas (marked in red).
I don't want them to be clustered all together near each other (the result of directly looking for top N points).
I would like these points to be spread all over the image (like shown bellow), with higher density where the values are high, and lower density where the values are low. I am looking for an efficient python algorithm for the task.
Thanks.
![[Image: VyBhJ43]](https://imgur.com/VyBhJ43)
RE: Maximas in grayscale image - scidam - Aug-13-2020
Take a look at scikit-image's peak_local_max function.
It has min_distance parameter which regulates density of max-points to be chosen.
RE: Maximas in grayscale image - yliats - Aug-13-2020
(Aug-13-2020, 11:59 AM)scidam Wrote: Take a look at scikit-image's peak_local_max function.
It has min_distance parameter which regulates density of max-points to be chosen.
This worked very nicely! One problem I had was that min_distance was ignored for clusters of pixels that had equal values (all of them were chosen, even though min_distance should have prevented that). This problem was solved by adding noise to the image before using peak_local_max.
Thanks.