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itkImageModelEstimatorBase.h
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itkImageModelEstimatorBase.h
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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkImageModelEstimatorBase.h
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef _itkImageModelEstimatorBase_h
#define _itkImageModelEstimatorBase_h
#include "itkLightProcessObject.h"
namespace itk
{
/** \class ImageModelEstimatorBase
* \brief Base class for model estimation from images used for classification.
*
* itkImageModelEstimatorBase is the base class for the ImageModelEstimator
* objects. It provides the basic function definitions that are inherent to
* a ImageModelEstimator objects.
*
* This is the SuperClass for the ImageModelEstimator framework. This is an
* abstract class defining an interface for all such objects
* available through the ImageModelEstimator framework in the ITK toolkit.
*
* The basic functionality of the ImageModelEstimator framework base class is to
* generate the models used in classification applications. It requires input
* images and a training image to be provided by the user.
* This object supports data handling of multiband images. The object
* accepts the input image in vector format only, where each pixel is a
* vector and each element of the vector corresponds to an entry from
* 1 particular band of a multiband dataset. A single band image is treated
* as a vector image with a single element for every vector. The classified
* image is treated as a single band scalar image.
*
* EstimateModels() is a pure virtual function making this an abstract class.
* The template parameter is the type of a membership function the
* ImageModelEstimator populates.
*
* A membership function represents a specific knowledge about
* a class. In other words, it should tell us how "likely" is that a
* measurement vector (pattern) belong to the class.
*
* As the method name indicates, you can have more than one membership
* function. One for each classes. The order you put the membership
* calculator becomes the class label for the class that is represented
* by the membership calculator.
*
*
* \ingroup ClassificationFilters
*/
template <class TInputImage,
class TMembershipFunction>
class ITK_EXPORT ImageModelEstimatorBase: public LightProcessObject
{
public:
/** Standard class typedefs. */
typedef ImageModelEstimatorBase Self;
typedef LightProcessObject Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Run-time type information (and related methods). */
itkTypeMacro(ImageModelEstimatorBase,LightProcessObject);
/** Set the number of classes. */
itkSetMacro(NumberOfModels, unsigned int);
/** Get the number of classes. */
itkGetConstReferenceMacro(NumberOfModels, unsigned int);
/** Type definitions for the membership function . */
typedef typename TMembershipFunction::Pointer MembershipFunctionPointer ;
typedef std::vector< MembershipFunctionPointer >
MembershipFunctionPointerVector;
/** Type definitions for the training image. */
typedef TInputImage InputImageType;
typedef typename TInputImage::Pointer InputImagePointer;
/** Type definitions for the training image. */
//typedef typename TTrainingImage::Pointer TrainingImagePointer;
/** Set the input image. */
itkSetObjectMacro(InputImage,InputImageType);
/** Get the input image. */
itkGetObjectMacro(InputImage,InputImageType);
/** Set the classified image. */
void SetMembershipFunctions(MembershipFunctionPointerVector
membershipFunctions)
{
m_MembershipFunctions = membershipFunctions;
}
/** Method to get mean */
const MembershipFunctionPointerVector GetMembershipFunctions() const
{
return m_MembershipFunctions;
}
/** Method to number of membership functions */
unsigned int GetNumberOfMembershipFunctions()
{
return static_cast<unsigned int>( m_MembershipFunctions.size() );
}
/** Method to reset the membership fucntion mean */
void DeleteAllMembershipFunctions()
{
m_MembershipFunctions.resize(0);
}
/** Stores a MembershipCalculator of a class in its internal vector */
unsigned int AddMembershipFunction(MembershipFunctionPointer function);
/** Define a virtual function to perform model generation from the input data
*/
void Update() ;
protected:
ImageModelEstimatorBase();
~ImageModelEstimatorBase();
void PrintSelf(std::ostream& os, Indent indent) const;
virtual void GenerateData();
private:
ImageModelEstimatorBase(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
unsigned int m_NumberOfModels;
/** Container to hold the membership functions */
MembershipFunctionPointerVector m_MembershipFunctions;
/**Container for holding the training image */
InputImagePointer m_InputImage;
/** The core virtual function to perform modelling of the input data */
virtual void EstimateModels() = 0;
}; // class ImageModelEstimator
} // namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkImageModelEstimatorBase.txx"
#endif
#endif