| Re: Distinguishing between point-like and curve-like features [message #82832 is a reply to message #82813] |
Tue, 15 January 2013 08:54  |
David Fanning
Messages: 11724
Registered: August 2001
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Senior Member |
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Mats Löfdahl writes:
>
> I'm making image masks that are supposed to take out certain small point-like features. These features are usually just a few pixels wide but sometimes as much as about ten or fifteen pixels wide. Because there are other, more large-scale variations in the image, I base the mask on a unsharp masked version of the image, to make the features I'm interested in stand out more. Then I clean the mask with a morph_open operation to get rid of some raggedness of the edges of
the "holes" in the mask.
>
> This has worked fine, but I now have some images that have, in addition to the small features that I want to take out, also some high-amplitude curved fringes with similar width that I do _not_ want the mask to take out.
>
> I'm wondering if anyone can suggest a strategy for automatically (and reasonably fast) distinguishing between the point-like and the curve-like features. The masks I'm making either take both out or none, depending on the choice of parameters.
>
> I'm not looking for code here, but maybe some good ideas.
>
> (If you want the background, I'm trying to make bad-pixel masks for some CCD cameras based on flat fields that have significant interference fringes. The small features I want to mask out are clusters of bad pixels, both from the detector itself and due to near-focus dust particles. The purpose of the mask is to identify pixels with no information, where I have to interpolate to get useful values in the science images. Useful in the sense that those pixels do not cause
ringing artifacts when I do deconvolution.)
Maybe you could fit the features with an ellipse. It is possible, I
suppose, that curved features will have more elliptical character than
point-like features.
http://www.idlcoyote.com/ip_tips/fit_ellipse.html
Cheers,
David
--
David Fanning, Ph.D.
Fanning Software Consulting, Inc.
Coyote's Guide to IDL Programming: http://www.idlcoyote.com/
Sepore ma de ni thue. ("Perhaps thou speakest truth.")
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