[Insight-developers] RecursiveGaussianImageFilter

[Luis Ibanez]

HI Gunnar,


It is very easy to run specific tests by using "ctest"
This is an utility that makes part of CMake.


Just go to the ITK binary directory and type


         ctest    -V    -R     name-of-test


The option "-V" is for "Verbose"
The option "-R" is for "Regular expression"

You can actually pass any regular expression to "ctest",
so you could do for example


    ctest  -V   -R   "itkImageRegistation*"

to run all the ImageRegistration tests.


Ctest will use the correct parameters that were specified
in the CMakeLists.txt file of the test.



You can also submit build to the Dashboard with minimal
effort. Just do:


          ctest -D Experimental



That will take care of everything: configuring, building,
running the tests and submitting the results to the Dashboard.



            ctest  -h

will give you a help summary.




    Regards,


       Luis



----------------------------------------------------
Gunnar Farneback wrote:

>>Embarrassingly enough it looks like I managed to mess up the
>>normalization across scales after all. Please find a new version at
>>http://lmi.bwh.harvard.edu/~gunnar/itk_recursive_gaussian.html
>>(only itkRecursiveGaussianImageFilter.txx has been changed).
> 
> 
> I have now found out how to run a single test by hand. Apparently
> itkRecursiveGaussianImageFiltersTest still fails the normalization
> across scales, although now it's at least close.
> 
> Now the question is what normalization across scales actually means.
> 
> 1. Judging from the testcase it means that the maximum impulse
>    response should be constant for the smoothing filter.
> 
> 2. A comment in SmoothingRecursiveGaussianImageFilter.cxx says:
> 
>    | There are two typical ways of normalizing Gaussians depending on their
>    | application. For scale-space analysis it is desirable to use a
>    | normalization that will preserve the maximum value of the input. This
> 
>    I'm not sure I can make sense of this but it seems difficult to do
>    in general without having an image dependent normalization.
> 
> 3. The documentation for the NormalizeAcrossScale flag in
>    itkRecursiveGaussianImageFilter.h says:
>    
>    | Set/Get the flag for normalizing the gaussian over scale space.
>    | When this flag is ON the filter will be normalized in such a way 
>    | that larger sigmas will not result in the image fading away.
> 
>    This is not very exact but possibly consistent with the regression
>    test.
> 
>    | \f[    
>    |       \frac{ 1 }{ \sqrt{ 2 \pi } };
>    | \f]
>    |
>    | When the flag is OFF the normalization will conserve contant the 
>    | integral of the image intensity. 
>    | \f[    
>    |       \frac{ 1 }{ \sigma  \sqrt{ 2 \pi } };
>    | \f]
> 
>    This normalization factor is only correct for the continuous
>    Gaussian. My implementation computes the normalization factor so
>    that the sum of the actual discrete infinite impulse response is
>    exactly one. From the equations above I then assumed that
>    multiplying the response by sigma when NormalizAcrossScale is ON
>    would be good enough.
> 
> So, how should the normalization across scale be implemented? I can
> certainly change so that 1. is fulfilled if that is what we want but
> what is the appropriate scaling in that case for the derivative
> filters? Where should I read or who should I ask to find out? Or is my
> implementation okay but the test should be changed instead?
> 
> Two more technical questions about running tests:
> 
> 1. I haven't found out how to run e.g. the
>    itkLaplacianRecursiveGaussianImageFilterTest by hand without having
>    to look in Testing/Code/BasicFilters/DartTestfile.txt for the
>    input file. I assume there is some mechanism that automates
>    running the tests.
> 
> 2. Is there some easy way to run a custom collection of tests, more
>    specifically the ones failing on
>    http://www.itk.org/Testing/Sites/zion.kitware/Linux-g++-3.3/20041206-1919-Experimental/Test.html ?
> 
> /Gunnar
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