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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 itkGradientMagnitudeRecursiveGaussianImageFilter_h
#define itkGradientMagnitudeRecursiveGaussianImageFilter_h
#include "itkNthElementImageAdaptor.h"
#include "itkImage.h"
#include "itkPixelTraits.h"
#include "itkRecursiveGaussianImageFilter.h"
#include "itkSqrtImageFilter.h"
#include "itkBinaryGeneratorImageFilter.h"
namespace itk
{
/**
* \class GradientMagnitudeRecursiveGaussianImageFilter
* \brief Computes the Magnitude of the Gradient of an image by convolution
* with the first derivative of a Gaussian.
*
* This filter is implemented using the recursive gaussian
* filters
*
* \ingroup GradientFilters
* \ingroup SingleThreaded
* \ingroup ITKImageGradient
*
* \sphinx
* \sphinxexample{Filtering/ImageGradient/ComputeGradientMagnitude,Compute Gradient Magnitude Of Grayscale Image}
* \endsphinx
*/
// NOTE that the typename macro has to be used here in lieu
// of "typename" because VC++ doesn't like the typename keyword
// on the defaults of template parameters
template <typename TInputImage, typename TOutputImage = TInputImage>
class ITK_TEMPLATE_EXPORT GradientMagnitudeRecursiveGaussianImageFilter
: public InPlaceImageFilter<TInputImage, TOutputImage>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(GradientMagnitudeRecursiveGaussianImageFilter);
/** Standard class type aliases. */
using Self = GradientMagnitudeRecursiveGaussianImageFilter;
using Superclass = InPlaceImageFilter<TInputImage, TOutputImage>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Pixel Type of the input image */
using InputImageType = TInputImage;
using PixelType = typename InputImageType::PixelType;
/** Image dimension. */
static constexpr unsigned int ImageDimension = TInputImage::ImageDimension;
using RealType = typename NumericTraits<PixelType>::RealType;
/** Define the image type for internal computations
RealType is usually 'double' in NumericTraits.
Here we prefer float in order to save memory. */
using InternalRealType = float;
using RealImageType = Image<InternalRealType, Self::ImageDimension>;
/** Smoothing filter type */
using GaussianFilterType = RecursiveGaussianImageFilter<RealImageType, RealImageType>;
/** Derivative filter type, it will be the first in the pipeline */
using DerivativeFilterType = RecursiveGaussianImageFilter<InputImageType, RealImageType>;
/** Smoothing filter type */
using SqrtFilterType = SqrtImageFilter<RealImageType, TOutputImage>;
/** Pointer to a gaussian filter. */
using GaussianFilterPointer = typename GaussianFilterType::Pointer;
/** Pointer to a derivative filter. */
using DerivativeFilterPointer = typename DerivativeFilterType::Pointer;
using SqrtFilterPointer = typename SqrtFilterType::Pointer;
/** Pointer to the Output Image */
using OutputImagePointer = typename TOutputImage::Pointer;
/** Type of the output Image */
using OutputImageType = TOutputImage;
using OutputPixelType = typename OutputImageType::PixelType;
/** Auxiliary image for holding the values of the squared gradient components
*/
using CumulativeImageType = Image<InternalRealType, Self::ImageDimension>;
using CumulativeImagePointer = typename CumulativeImageType::Pointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(GradientMagnitudeRecursiveGaussianImageFilter);
/** Set/Get Sigma value. Sigma is measured in the units of image spacing. */
void
SetSigma(RealType sigma);
RealType
GetSigma();
/** Set/Get the normalization factor that will be used for the Gaussian.
*
* \sa RecursiveGaussianImageFilter::SetNormalizeAcrossScale
*/
void
SetNormalizeAcrossScale(bool normalize);
itkGetConstMacro(NormalizeAcrossScale, bool);
itkBooleanMacro(NormalizeAcrossScale);
void
SetNumberOfWorkUnits(ThreadIdType nb) override;
#ifdef ITK_USE_CONCEPT_CHECKING
// Begin concept checking
itkConceptMacro(InputHasNumericTraitsCheck, (Concept::HasNumericTraits<PixelType>));
// End concept checking
#endif
protected:
GradientMagnitudeRecursiveGaussianImageFilter();
~GradientMagnitudeRecursiveGaussianImageFilter() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
/** Generate Data */
void
GenerateData() override;
/** GradientMagnitudeRecursiveGaussianImageFilter needs all of the
* input to produce an output. Therefore,
* GradientMagnitudeRecursiveGaussianImageFilter needs to provide an
* implementation for GenerateInputRequestedRegion in order to
* inform the pipeline execution model. \sa
* ImageToImageFilter::GenerateInputRequestedRegion() */
void
GenerateInputRequestedRegion() override;
/** GradientMagnitudeRecursiveGaussianImageFilter produces all of
* the output. Therefore, it needs to provide an implementation of
* EnlargeOutputRequestedRegion(). */
void
EnlargeOutputRequestedRegion(DataObject * output) override;
private:
using SqrSpacingFilterType = BinaryGeneratorImageFilter<RealImageType, RealImageType, RealImageType>;
using SqrSpacingFilterPointer = typename SqrSpacingFilterType::Pointer;
GaussianFilterPointer m_SmoothingFilters[ImageDimension - 1]{};
DerivativeFilterPointer m_DerivativeFilter{};
SqrSpacingFilterPointer m_SqrSpacingFilter{};
SqrtFilterPointer m_SqrtFilter{};
/** Normalize the image across scale space */
bool m_NormalizeAcrossScale{};
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkGradientMagnitudeRecursiveGaussianImageFilter.hxx"
#endif
#endif
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