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/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkBinaryStatisticsOpeningImageFilter_h
#define itkBinaryStatisticsOpeningImageFilter_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:
* https://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
* \ingroup ITKLabelMap
*
* \sphinx
* \sphinxexample{Filtering/LabelMap/KeepBinaryRegionsThatMeetSpecific,Keep Binary Regions That Meet Specific
* Properties} \endsphinx
*/
template <typename TInputImage, typename TFeatureImage>
class ITK_TEMPLATE_EXPORT BinaryStatisticsOpeningImageFilter : public ImageToImageFilter<TInputImage, TInputImage>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(BinaryStatisticsOpeningImageFilter);
/** Standard class type aliases. */
using Self = BinaryStatisticsOpeningImageFilter;
using Superclass = ImageToImageFilter<TInputImage, TInputImage>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Some convenient type alias. */
using InputImageType = TInputImage;
using OutputImageType = TInputImage;
using InputImagePointer = typename InputImageType::Pointer;
using InputImageConstPointer = typename InputImageType::ConstPointer;
using InputImageRegionType = typename InputImageType::RegionType;
using InputImagePixelType = typename InputImageType::PixelType;
using OutputImagePointer = typename OutputImageType::Pointer;
using OutputImageConstPointer = typename OutputImageType::ConstPointer;
using OutputImageRegionType = typename OutputImageType::RegionType;
using OutputImagePixelType = typename OutputImageType::PixelType;
using FeatureImageType = TFeatureImage;
using FeatureImagePointer = typename FeatureImageType::Pointer;
using FeatureImageConstPointer = typename FeatureImageType::ConstPointer;
using FeatureImagePixelType = typename FeatureImageType::PixelType;
/** ImageDimension constants */
static constexpr unsigned int InputImageDimension = TInputImage::ImageDimension;
static constexpr unsigned int OutputImageDimension = TInputImage::ImageDimension;
static constexpr unsigned int ImageDimension = TInputImage::ImageDimension;
using LabelType = SizeValueType;
using LabelObjectType = StatisticsLabelObject<LabelType, Self::ImageDimension>;
using LabelMapType = LabelMap<LabelObjectType>;
using LabelizerType = BinaryImageToLabelMapFilter<InputImageType, LabelMapType>;
using LabelObjectValuatorType = StatisticsLabelMapFilter<LabelMapType, FeatureImageType>;
using AttributeType = typename LabelObjectType::AttributeType;
using OpeningType = StatisticsOpeningLabelMapFilter<LabelMapType>;
using BinarizerType = LabelMapToBinaryImageFilter<LabelMapType, OutputImageType>;
/** Standard New method. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(BinaryStatisticsOpeningImageFilter);
/**
* 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() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
/** BinaryStatisticsOpeningImageFilter needs the entire input to be available.
* Thus, it needs to provide an implementation of GenerateInputRequestedRegion(). */
void
GenerateInputRequestedRegion() override;
/** BinaryStatisticsOpeningImageFilter will produce the entire output. */
void
EnlargeOutputRequestedRegion(DataObject * itkNotUsed(output)) override;
/** Single-threaded version of GenerateData. This filter delegates
* to GrayscaleGeodesicErodeImageFilter. */
void
GenerateData() override;
private:
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.hxx"
#endif
#endif
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