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Convolution applied on an image

My final goal is to improve our microscope images by deconvolution using the point spread function (PSF). Because I got unexpected results I started with testing the basic procedures. In a first attempt I tried to fold (=convolute) the image of a single point with the PSF. If the PSF is also represented as a single point ( pixel value there = 1, elsewhere = 0), the result should be the same as the original image (one single point). I can get that using ImageJ from NIH. With Labview, I wanted to follow the convolution theorem (Wiener Khintchine): f o g = F-1 (F f * F g) where f and g are the images of the single point and of the PSF resp.
F and F-1 are the Fourier Transformation and its inverse. Obviously multiplying has to be done wi
th ComplexMultiply. I tried it with and without using ComplexFlipFrequency (when is that needed, when not?!?!), with and without normalizing the pixel sum of the PSF to 1, but I get only zeros or small values everywhere in the resulting image. What is wrong with this rather straightforward concept?
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Hi,

you can find an example in the attachement, which
displays the functionality of "ComplexFlipFrequency". You also will find a pic which displays the difference from the FFT of a "big" and a "little" white point!

Your application cannot work, because you take two pics which have both the color black, so a convolution with the value "0" equals "0".

regards
Thomas Sandrisser
NI Germany
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Hi Thomas,
thank you for your example file. Unfortunately I forgot to mention that I still use LV Version 6.02 (poor university!), so I cannot run it.
My test images are not zero everywhere. The PointiIdeal1 has a center pixel with value 1000, the PSF a center value of 779 surrounded by pixels with decaying values. It really works as you can see in the attached picture collection produced with ImageJ. The single point folded with the PSF results in the PSF as awaited from theory. So this job should also be done by IMAQ Vision.
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Hi,

i've tested here something in addition with matlab (image processing toolbox) - so, i think it's the best way, when you send me an email (thomas.sandrisser@ni.com) for further informations...

regards,
Thomas Sandrisser
Ni Germany
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