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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkBinaryStatisticsOpeningImageFilter.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 __itkBinaryStatisticsOpeningImageFilter_h
#define __itkBinaryStatisticsOpeningImageFilter_h
#include "itkImageToImageFilter.h"
#include "itkStatisticsLabelObject.h"
#include "itkLabelMap.h"
#include "itkBinaryImageToLabelMapFilter.h"
#include "itkStatisticsLabelMapFilter.h"
#include "itkStatisticsOpeningLabelMapFilter.h"
#include "itkLabelMapToBinaryImageFilter.h"
namespace itk {
/** \class BinaryStatisticsOpeningImageFilter
* \brief Remove objects based on the value of their Statistics attribute.
*
* The BinaryStatisticsOpeningImageFilter removes the objects in a binary image
* with an attribute value smaller or greater than a threshold called Lambda.
* The attributes are those of the StatisticsLabelObject.
*
* This implementation was taken from the Insight Journal paper:
* http://hdl.handle.net/1926/584 or
* http://www.insight-journal.org/browse/publication/176
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
* \sa StatisticsLabelObject, LabelStatisticsOpeningImageFilter, BinaryStatisticsOpeningImageFilter
* \ingroup ImageEnhancement MathematicalMorphologyImageFilters
*/
template<class TInputImage, class TFeatureImage>
class ITK_EXPORT BinaryStatisticsOpeningImageFilter :
public ImageToImageFilter<TInputImage, TInputImage>
{
public:
/** Standard class typedefs. */
typedef BinaryStatisticsOpeningImageFilter Self;
typedef ImageToImageFilter<TInputImage, TInputImage> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Some convenient typedefs. */
typedef TInputImage InputImageType;
typedef TInputImage OutputImageType;
typedef typename InputImageType::Pointer InputImagePointer;
typedef typename InputImageType::ConstPointer InputImageConstPointer;
typedef typename InputImageType::RegionType InputImageRegionType;
typedef typename InputImageType::PixelType InputImagePixelType;
typedef typename OutputImageType::Pointer OutputImagePointer;
typedef typename OutputImageType::ConstPointer OutputImageConstPointer;
typedef typename OutputImageType::RegionType OutputImageRegionType;
typedef typename OutputImageType::PixelType OutputImagePixelType;
typedef TFeatureImage FeatureImageType;
typedef typename FeatureImageType::Pointer FeatureImagePointer;
typedef typename FeatureImageType::ConstPointer FeatureImageConstPointer;
typedef typename FeatureImageType::PixelType FeatureImagePixelType;
/** ImageDimension constants */
itkStaticConstMacro(InputImageDimension, unsigned int, TInputImage::ImageDimension);
itkStaticConstMacro(OutputImageDimension, unsigned int, TInputImage::ImageDimension);
itkStaticConstMacro(ImageDimension, unsigned int, TInputImage::ImageDimension);
typedef StatisticsLabelObject<unsigned long, itkGetStaticConstMacro(ImageDimension)> LabelObjectType;
typedef LabelMap< LabelObjectType > LabelMapType;
typedef BinaryImageToLabelMapFilter< InputImageType, LabelMapType > LabelizerType;
typedef StatisticsLabelMapFilter< LabelMapType, FeatureImageType > LabelObjectValuatorType;
typedef typename LabelObjectType::AttributeType AttributeType;
typedef StatisticsOpeningLabelMapFilter< LabelMapType > OpeningType;
typedef LabelMapToBinaryImageFilter< LabelMapType, OutputImageType > BinarizerType;
/** Standard New method. */
itkNewMacro(Self);
/** Runtime information support. */
itkTypeMacro(BinaryStatisticsOpeningImageFilter, ImageToImageFilter );
/**
* Set/Get whether the connected components are defined strictly by
* face connectivity or by face+edge+vertex connectivity.
* Default is FullyConnectedOff.
* For objects that are 1 pixel wide, use FullyConnectedOn.
*/
itkSetMacro( FullyConnected, bool );
itkGetConstReferenceMacro( FullyConnected, bool );
itkBooleanMacro( FullyConnected );
#ifdef ITK_USE_CONCEPT_CHECKING
/** Begin concept checking */
itkConceptMacro(InputEqualityComparableCheck,
(Concept::EqualityComparable<InputImagePixelType>));
itkConceptMacro(IntConvertibleToInputCheck,
(Concept::Convertible<int, InputImagePixelType>));
itkConceptMacro(InputOStreamWritableCheck,
(Concept::OStreamWritable<InputImagePixelType>));
/** End concept checking */
#endif
/**
* Set/Get the value used as "background" in the output image.
* Defaults to NumericTraits<PixelType>::NonpositiveMin().
*/
itkSetMacro( BackgroundValue, OutputImagePixelType );
itkGetConstMacro( BackgroundValue, OutputImagePixelType );
/**
* Set/Get the value used as "foreground" in the output image.
* Defaults to NumericTraits<PixelType>::max().
*/
itkSetMacro( ForegroundValue, OutputImagePixelType );
itkGetConstMacro( ForegroundValue, OutputImagePixelType);
/**
* Set/Get the threshold used to keep or remove the objects.
*/
itkGetConstMacro( Lambda, double );
itkSetMacro( Lambda, double );
/**
* Set/Get the ordering of the objects. By default, the objects with
* an attribute value smaller than Lamba are removed. Turning ReverseOrdering
* to true make this filter remove objects with an attribute value greater
* than Lambda instead.
*/
itkGetConstMacro( ReverseOrdering, bool );
itkSetMacro( ReverseOrdering, bool );
itkBooleanMacro( ReverseOrdering );
/**
* Set/Get the attribute to use to select the object to remove.
* Default is "Size".
*/
itkGetConstMacro( Attribute, AttributeType );
itkSetMacro( Attribute, AttributeType );
void SetAttribute( const std::string & s )
{
this->SetAttribute( LabelObjectType::GetAttributeFromName( s ) );
}
/** Set the feature image */
void SetFeatureImage(const TFeatureImage *input)
{
// Process object is not const-correct so the const casting is required.
this->SetNthInput( 1, const_cast<TFeatureImage *>(input) );
}
/** Get the feature image */
const FeatureImageType * GetFeatureImage()
{
return static_cast<const FeatureImageType*>(this->ProcessObject::GetInput(1));
}
/** Set the input image */
void SetInput1(const InputImageType *input)
{
this->SetInput( input );
}
/** Set the feature image */
void SetInput2(const FeatureImageType *input)
{
this->SetFeatureImage( input );
}
protected:
BinaryStatisticsOpeningImageFilter();
~BinaryStatisticsOpeningImageFilter() {}
void PrintSelf( std::ostream& os, Indent indent ) const;
/** BinaryStatisticsOpeningImageFilter needs the entire input to be available.
* Thus, it needs to provide an implementation of GenerateInputRequestedRegion(). */
void GenerateInputRequestedRegion();
/** BinaryStatisticsOpeningImageFilter will produce the entire output. */
void EnlargeOutputRequestedRegion( DataObject *itkNotUsed(output) );
/** Single-threaded version of GenerateData. This filter delegates
* to GrayscaleGeodesicErodeImageFilter. */
void GenerateData();
private:
BinaryStatisticsOpeningImageFilter( const Self& ); //purposely not implemented
void operator=( const Self& ); //purposely not implemented
bool m_FullyConnected;
OutputImagePixelType m_BackgroundValue;
OutputImagePixelType m_ForegroundValue;
double m_Lambda;
bool m_ReverseOrdering;
AttributeType m_Attribute;
}; // end of class
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkBinaryStatisticsOpeningImageFilter.txx"
#endif
#endif
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