On 4 Apr., 06:53, "Terry Duell" <[email protected]> wrote:

> > On Sun, 03 Apr 2011 21:12:00 +1000, kfj <[email protected]> wrote:
> > convolution in the 'time' domain (btw. where is time in a 2D
> > matrix ;-)

> Sorry A terminology mix up on my part. For this sort of stuff I should be
> using the terms 'spatial' and 'frequency' domain, although 'time' domain
> seems to be applied quite a lot to that which isn't the frequency domain
> regardless of the nature of the problem. I think time can be considered
> the same as distance in this sort of stuff.

It's from signal-processing one-dimensional signals, which usually
vary with time - like sounds. That's where the whole Fourier stuff
started out, decomposing periodic phenomena into harmonics.

> > And I still believe those sharp discontinuities and minimum-to-maximum
> > jumps in your source image may be part of the problem, never mind you
> > can recover the source image precisely.
>
> Things are now looking a bit more like they should.
> I found some basic errors in the way I was doing convolution and  
> deconvolution in freq domain in Octave. I had forgotten that special  
> syntax is needed for element by element multiply and divide when dealing  
> with arrays/matrices. A bit more RTFM needed!
> I also 'toned' down the test image a tad.
> The sharp image can now be recovered (almost) exactly, and applying the  
> same PSF to the sharp recovers the blurred image (almost) exactly.
> The 'brightness' of the recovered images (the pixel values) don't come  
> back exactly as they go in, but the ratios seem to be the same.
> In the attached images I have rescaled the derived images to have the same  
> max values as the originals.

Well done! Once the simple test case works, you can at least hope more
complex signals will yield as well - maybe not perfectly, but to a
degree. Best of luck. I'll be off on a holiday - who knows maybe
you'll have it all sorted by the time I'm back!

Kay

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