[Insight-users] Problems with bilateral filtering

[Bill Lorensen]

You should get the same results, but I have not checked this.

Bill

On Wed, Jun 23, 2010 at 6:03 AM, Stuart Golodetz <itk at gxstudios.net> wrote:
> Ah ok - thanks. Would you otherwise expect the 2D and 3D versions to produce
> exactly the same output? (If so, I might switch to using the 2D version when
> the volume I'm smoothing is essentially 2D.)
>
> Cheers,
> Stu
>
> Bill Lorensen wrote:
>>
>> Yes, boundary checking slows it down.
>>
>> On Tue, Jun 22, 2010 at 3:18 PM, Stuart Golodetz <itk at gxstudios.net>
>> wrote:
>>
>>>
>>> Stuart Golodetz wrote:
>>>
>>>>
>>>> Hi,
>>>>
>>>> I think I may be having some trouble using BilateralImageFilter
>>>> appropriately and just thought I should check. Essentially, I'm trying
>>>> it
>>>> out as a replacement to multiple iterations of anisotropic diffusion
>>>> filtering for edge-preserving smoothing of my input image, using the
>>>> following code:
>>>>
>>>> ###
>>>> ...
>>>> typedef itk::BilateralImageFilter<RealImage,RealImage> BilateralFilter;
>>>> BilateralFilter::Pointer bilateralFilter = BilateralFilter::New();
>>>> bilateralFilter->SetInput(realImage);
>>>> double domainSigmas[] = {6.0,6.0,6.0};   // test values (not connected
>>>> to
>>>> the GUI yet)
>>>> double rangeSigma = 5.0;   // ditto
>>>> bilateralFilter->SetDomainSigma(domainSigmas);
>>>> bilateralFilter->SetRangeSigma(rangeSigma);
>>>> bilateralFilter->Update();
>>>> realImage = bilateralFilter->GetOutput();
>>>>
>>>> if(is_aborted()) return;
>>>> increment_progress();
>>>> ...
>>>> ###
>>>>
>>>> I was hoping it was going to be faster than the anisotropic filtering
>>>> I'm
>>>> currently doing, as that takes about a second per iteration per 512x512
>>>> slice (i.e. 30 seconds per slice for 30 iterations, which is not ideal):
>>>>
>>>> ###
>>>> ...
>>>> // Smooth this real image using anisotropic diffusion filtering.
>>>> typedef
>>>> itk::GradientAnisotropicDiffusionImageFilter<RealImage,RealImage>
>>>> ADFilter;
>>>> for(int i=0; i<m_segmentationOptions.adfIterations; ++i)
>>>> {
>>>>  ADFilter::Pointer adFilter = ADFilter::New();
>>>>  adFilter->SetInput(realImage);
>>>>  adFilter->SetConductanceParameter(1.0);   // test value (not connected
>>>> to the GUI yet)
>>>>  adFilter->SetNumberOfIterations(1);   // done this way so that I can
>>>> update the progress after each iteration
>>>>  adFilter->SetTimeStep(0.0625);
>>>>  adFilter->Update();
>>>>  realImage = adFilter->GetOutput();
>>>>
>>>>  if(is_aborted()) return;
>>>>  increment_progress();
>>>> }
>>>> ...
>>>> ###
>>>>
>>>> Unfortunately, it takes 3 minutes for a 512x512 slice, whilst producing
>>>> "worse" results (in my context) than the anisotropic diffusion filtering
>>>> I
>>>> was doing before. So I have three questions:
>>>>
>>>> 1) Would you expect bilateral image filtering to take this long? If not,
>>>> do you have any idea what I might be doing wrong please? (If not, is
>>>> there
>>>> anything I can investigate to try and track down the problem myself?)
>>>> 2) Are the domain and range parameters having any effect on this, and
>>>> how
>>>> should I go about setting them appropriately please?
>>>> 3) Am I barking up the wrong tree by trying to use bilateral image
>>>> filtering as a drop-in alternative to anisotropic diffusion filtering
>>>> like
>>>> this?
>>>>
>>>> Cheers,
>>>> Stu
>>>>
>>>
>>> A separate (but related) question I have is: why would 3D anisotropic
>>> diffusion filtering on a 512x512x1 volume be substantially slower than 2D
>>> anisotropic diffusion filtering on a 512x512 slice? I know the time step
>>> has
>>> to be smaller for the 3D version, but I recall it still being
>>> substantially
>>> slower than before. However, 3D anisotropic diffusion filtering on a
>>> larger
>>> volume e.g. 512x512x20 wasn't all that slow considering what it was
>>> doing. I
>>> was wondering whether boundary checking might be slowing it down? Or is
>>> there actually some other reason I haven't thought of?
>>>
>>> Cheers,
>>> Stu
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