[Insight-users] Re: itk Gradient Descent Optimizer : Mixture modeling ?
Luis Ibanez
luis.ibanez@kitware.com
Wed, 23 Oct 2002 15:15:26 -0400
Hi digvijay,
What you are doing looks like a good fit
for Mixture Modeling. That is, fitting a
set of Gaussians to an histogram.
You may want to take a look at the Statistics
package and Classification Framework in ITK.
This can be found at
Insight/Code/Numerics/Statistics
and
Insight/Code/Algorithms
The following classes could be good start
GoodnessOfFitMixtureModelCostFunction
http://www.itk.org/Insight/Doxygen/html/classitk_1_1Statistics_1_1GoodnessOfFitMixtureModelCostFunction.html
MixtureModelEstimator
http://www.itk.org/Insight/Doxygen/html/classitk_1_1Statistics_1_1ExpectationMaximizationMixtureModelEstimator.html
GaussianMixtureModelComponent
http://www.itk.org/Insight/Doxygen/html/classitk_1_1Statistics_1_1GaussianMixtureModelComponent.html
SampleClassifier
http://www.itk.org/Insight/Doxygen/html/classitk_1_1Statistics_1_1SampleClassifier.html
TableLookupSampleClassifier
http://www.itk.org/Insight/Doxygen/html/classitk_1_1Statistics_1_1TableLookupSampleClassifier.html
Please let us know if you have further questions,
Thanks
Luis
=======================================================
digvijay singh wrote:
> hi luis!!
> i get the emphasis on const......and the optimizer
> does not implement constraints....bad news for me :-),
> now i am trying to read in an image compute its
> histogram and model it as a sum of gaussian functions.
> The model gets good enough values for the
> initialization from histogram computation as one of
> the gaussians is predominant over the rest. I was
> trying to minimize the error in the fit starting with
> a single gaussian but i need to impose constraints on
> the way the optimization progresses simply because i
> wish to compute it for the predominant gaussian first.
> That's my side of story....thanks for your help
> ciao
> digvijay
>
>
>