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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 itkStatisticsLabelMapFilter_h
#define itkStatisticsLabelMapFilter_h
#include "itkShapeLabelMapFilter.h"
namespace itk
{
/**
* \class StatisticsLabelMapFilter
* \brief The valuator class for the StatisticsLabelObject
*
* StatisticsLabelMapFilter can be used to set the attributes values
* of the StatisticsLabelObject in a LabelMap.
*
* \author Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.
*
* This implementation was taken from the Insight Journal paper:
* https://www.insight-journal.org/browse/publication/176
*
* \ingroup ImageEnhancement MathematicalMorphologyImageFilters
* \ingroup ITKLabelMap
*/
template <typename TImage, typename TFeatureImage>
class ITK_TEMPLATE_EXPORT StatisticsLabelMapFilter
: public ShapeLabelMapFilter<TImage, Image<typename TImage::PixelType, TImage::ImageDimension>>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(StatisticsLabelMapFilter);
/** Standard class type aliases. */
using Self = StatisticsLabelMapFilter;
using Superclass = ShapeLabelMapFilter<TImage>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Some convenient type alias. */
using ImageType = TImage;
using ImagePointer = typename ImageType::Pointer;
using ImageConstPointer = typename ImageType::ConstPointer;
using PixelType = typename ImageType::PixelType;
using IndexType = typename ImageType::IndexType;
using PointType = typename ImageType::PointType;
using LabelObjectType = typename ImageType::LabelObjectType;
using MatrixType = typename LabelObjectType::MatrixType;
using VectorType = typename LabelObjectType::VectorType;
using FeatureImageType = TFeatureImage;
using FeatureImagePointer = typename FeatureImageType::Pointer;
using FeatureImageConstPointer = typename FeatureImageType::ConstPointer;
using FeatureImagePixelType = typename FeatureImageType::PixelType;
/** ImageDimension constants */
static constexpr unsigned int ImageDimension = TImage::ImageDimension;
/** Standard New method. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(StatisticsLabelMapFilter);
#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 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 */
FeatureImageType *
GetFeatureImage()
{
return static_cast<FeatureImageType *>(const_cast<DataObject *>(this->ProcessObject::GetInput(1)));
}
/** Set the input image */
void
SetInput1(TImage * input)
{
this->SetInput(input);
}
/** Set the feature image */
void
SetInput2(const TFeatureImage * input)
{
this->SetFeatureImage(input);
}
/**
* Set/Get whether the histogram should be attached to the label object or not.
* This option defaults to `true`, but because the histogram may take a lot of memory
* compared to the other attributes, this option is useful to reduce the memory usage
* when the histogram is not required.
*/
itkSetMacro(ComputeHistogram, bool);
itkGetConstReferenceMacro(ComputeHistogram, bool);
itkBooleanMacro(ComputeHistogram);
/**
* Set/Get the number of bins in the histogram. Note that the histogram is used
* to compute the median value, and that this option may have an effect on the
* value of the median.
*/
itkSetMacro(NumberOfBins, unsigned int);
itkGetConstReferenceMacro(NumberOfBins, unsigned int);
// Set the default number of bins to match the number of values for 8 or 16-bit integers; otherwise 128
static constexpr unsigned int
GetDefaultNumberOfBins()
{
constexpr size_t bitsShift = std::min(8 * sizeof(FeatureImagePixelType), 8 * sizeof(m_NumberOfBins) - 1);
return std::is_integral_v<FeatureImagePixelType> && sizeof(FeatureImagePixelType) <= 2 ? 1u << bitsShift : 128u;
}
protected:
StatisticsLabelMapFilter();
~StatisticsLabelMapFilter() override = default;
void
ThreadedProcessLabelObject(LabelObjectType * labelObject) override;
void
BeforeThreadedGenerateData() override;
void
PrintSelf(std::ostream & os, Indent indent) const override;
private:
FeatureImagePixelType m_Minimum{};
FeatureImagePixelType m_Maximum{};
unsigned int m_NumberOfBins{ GetDefaultNumberOfBins() };
bool m_ComputeHistogram{ true };
}; // end of class
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkStatisticsLabelMapFilter.hxx"
#endif
#endif
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