<div>Hello</div>Extracted from the itk doxygen documentation:<div><br></div><div><span class="Apple-style-span" style="font-family: Geneva, Arial, Helvetica, sans-serif; "><i>As compared to </i><a class="el" href="http://www.itk.org/Doxygen318/html/classitk_1_1DiscreteGaussianImageFilter.html" title="Blurs an image by separable convolution with discrete gaussian kernels. This filter..." style="color: rgb(26, 65, 168); text-decoration: none; "><i>itk::DiscreteGaussianImageFilter</i></a><i>, this filter (</i></span><i>RecursiveGaussianImageFilter) </i><span class="Apple-style-span" style="font-family: Geneva, Arial, Helvetica, sans-serif; "><i>tends to be faster for large kernels, and it can take the derivative of the blurred image in one step. </i></span></div>
<div><span class="Apple-style-span" style="font-family: Geneva, Arial, Helvetica, sans-serif; "><br></span></div><div><span class="Apple-style-span" style="font-family: Geneva, Arial, Helvetica, sans-serif; ">so if you are using smaller sigmas and hence, smaller Gaussians, DiscreteGaussianImageFilter may result in faster execution time.</span></div>
<div><span class="Apple-style-span" style="font-family: Geneva, Arial, Helvetica, sans-serif; "><br></span></div><div><span class="Apple-style-span" style="font-family: Geneva, Arial, Helvetica, sans-serif; ">And now I'm speculating but my guess is that 1 second to perform 3x256x256x22 convolutions is not dramatically slow (it seems reasonable, as those represents more than 4 millions of convolution operations), but i don't know if it can be done much more faster.</span></div>
<div><span class="Apple-style-span" style="font-family: Geneva, Arial, Helvetica, sans-serif; font-size: 14px; "><br></span></div><div><span class="Apple-style-span" style="font-family: Geneva, Arial, Helvetica, sans-serif; font-size: 14px; "><br>
</span></div><div><br><div class="gmail_quote">On Wed, Jun 16, 2010 at 3:41 PM, Merrem, Andreas <span dir="ltr"><<a href="mailto:andreas.merrem@medma.uni-heidelberg.de">andreas.merrem@medma.uni-heidelberg.de</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">Hi Bill and Sergio,<br>
<br>
Thank you for your answers.<br>
<br>
I tried using nth element adaptors and the VectorIndexSelectionCastImageFilter, but it doesn't make it faster, what takes time is really the smoothing itself (as you already expected).<br>
<br>
Yes, I built both the itk library and the application in release mode. Do you think a second is a reasonable amount of time for smoothing 3 image volumes of size 256*256*22?<br>
<br>
If anyone knows a smoothing filter that does Gaussian smoothing and works faster than the itk recursive filter (perhaps something in frequency space) that would be a great help.<br>
<br>
<br>
<br>
<br>
<br>
-----Ursprüngliche Nachricht-----<br>
Von: Bill Lorensen [mailto:<a href="mailto:bill.lorensen@gmail.com">bill.lorensen@gmail.com</a>]<br>
Gesendet: Dienstag, 15. Juni 2010 20:12<br>
An: Merrem, Andreas<br>
Cc: Luis Ibanez; <a href="mailto:insight-users@itk.org">insight-users@itk.org</a><br>
Betreff: Re: [Insight-users] Smoothing Vector Images<br>
<div><div></div><div class="h5"><br>
First question: are you building ITK and your app with Release?<br>
<br>
On Tue, Jun 15, 2010 at 11:34 AM, Merrem, Andreas <<a href="mailto:andreas.merrem@medma.uni-heidelberg.de">andreas.merrem@medma.uni-heidelberg.de</a>> wrote:<br>
> Hi Luis, hi everyone,<br>
><br>
> I am trying to smooth 3D image volumes of size 256 * 256 * 22 pixels,<br>
> in which each pixel contains a 3 dimensional itk::CovariantVector. The<br>
> vector components should be smoothed independently over the whole<br>
> volume. My current solution is to first copy the 3 vector components<br>
> in each pixel into<br>
> 3 separate images with pixel type float, then use the<br>
> itk::RecursiveGaussianImageFilter for smoothing on all 3 images, and<br>
> finally copy the pixel values of the smoothed images back into the<br>
> covariant vector image.<br>
><br>
> My problem is that this procedure takes about one second. As a part of<br>
> a registration program, this leads to extremely slow registration<br>
> (about 10 minutes for one 256*256*22 dicom volume). Is there a way to<br>
> use less memory by avoiding the copying, or do you know a different,<br>
> faster technique of applying a Gaussian filter?<br>
><br>
> Thanks a lot,<br>
><br>
> Andreas<br>
><br>
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