[ITK] [ITK Community] Speeding up Cross Correlation

[Matt McCormick]

Hi Arjun,

Since computing an FFT requires all of an image, you cannot speed up
this algorithm even if only part of the output is required.

Some other options:

  ConvolutionImageFilter [1]

  A cross correlation metric [2].

Hope this helps,
Matt

[1] http://www.itk.org/Doxygen/html/classitk_1_1ConvolutionImageFilter.html

[2] http://www.itk.org/Doxygen/html/classitk_1_1CorrelationImageToImageMetricv4.html

On Fri, Nov 21, 2014 at 1:18 PM, Arjun S Kumar <arjun89 at cmu.edu> wrote:
> Hi all,
>
> I am trying to cross correlate two images such that the output image displays the similarity of the first image and the second image as a function of the translation of the second image.
>
> Currently, I'm using the itk::FFTNormalizedCorrelationImageFilter class. However, only a small portion, close to the center, of the output image is relevant for me. For example, for two images of sizes 500x500, the output image is about 1000x1000. However, I only need a 50x50 portion of the output image, centered at the center of the output image.
>
> So my question is, can I use this fact to perform the cross correlation faster? I tried using the SetRequiredNumberOfOverlappingPixels method to discard regions outside the 50x50 portion of the image but this didn't have a discernible effect on the speed of the operation. Shouldn't setting the required number of overlapping pixels to a high number decrease the time needed by reducing the domain of the output image?
>
> Is there a different way to manually set the size of the output image so that the computation is made faster? Can I change the requested region of the output image, just as we can do for input images?
>
> Are there other ITK classes that are more suited for this purpose. Does anybody recommend using neighborhood iterators? The problem I see with this is using a 500x500 neighborhood, which is too high isn't it?
>
> Please let me know.
>
> Thanks,
>
> Arjun
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