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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 itkAdditiveGaussianNoiseImageFilter_h
#define itkAdditiveGaussianNoiseImageFilter_h
#include "itkNoiseBaseImageFilter.h"
namespace itk
{
/**
* \class AdditiveGaussianNoiseImageFilter
*
* \brief Alter an image with additive Gaussian white noise.
*
* Additive Gaussian white noise can be modeled as:
*
* \par
* \f$ I = I_0 + N \f$
*
* \par
* where \f$ I \f$ is the observed image, \f$ I_0 \f$ is the noise-free image
* and \f$ N \f$ is a normally distributed random variable of mean \f$ \mu \f$
* and variance \f$ \sigma^2 \f$:
*
* \par
* \f$ N \sim \mathcal{N}(\mu, \sigma^2) \f$
*
* The noise is independent of the pixel intensities.
*
* \author Gaetan Lehmann
*
* This code was contributed in the Insight Journal paper "Noise
* Simulation". https://www.insight-journal.org/browse/publication/721
*
* \ingroup ITKImageNoise
*/
template <class TInputImage, class TOutputImage = TInputImage>
class ITK_TEMPLATE_EXPORT AdditiveGaussianNoiseImageFilter : public NoiseBaseImageFilter<TInputImage, TOutputImage>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(AdditiveGaussianNoiseImageFilter);
/** Standard class type aliases. */
using Self = AdditiveGaussianNoiseImageFilter;
using Superclass = NoiseBaseImageFilter<TInputImage, TOutputImage>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(AdditiveGaussianNoiseImageFilter);
/** Superclass type alias. */
using typename Superclass::OutputImageType;
using typename Superclass::OutputImagePointer;
using typename Superclass::OutputImageRegionType;
using typename Superclass::OutputImagePixelType;
/** Some convenient type alias. */
using InputImageType = TInputImage;
using InputImagePointer = typename InputImageType::Pointer;
using InputImageConstPointer = typename InputImageType::ConstPointer;
using InputImageRegionType = typename InputImageType::RegionType;
using InputImagePixelType = typename InputImageType::PixelType;
/** Set/Get the mean of the Gaussian distribution.
* Defaults to 0.0. */
itkGetConstMacro(Mean, double);
itkSetMacro(Mean, double);
/** Set/Get the standard deviation of the Gaussian distribution.
* Defaults to 1.0. */
itkGetConstMacro(StandardDeviation, double);
itkSetMacro(StandardDeviation, double);
#ifdef ITK_USE_CONCEPT_CHECKING
/** Begin concept checking */
itkConceptMacro(InputConvertibleToOutputCheck,
(Concept::Convertible<typename TInputImage::PixelType, typename TOutputImage::PixelType>));
/** End concept checking */
#endif
protected:
AdditiveGaussianNoiseImageFilter();
~AdditiveGaussianNoiseImageFilter() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
void
ThreadedGenerateData(const OutputImageRegionType & outputRegionForThread, ThreadIdType threadId) override;
private:
double m_Mean{ 0.0 };
double m_StandardDeviation{ 1.0 };
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkAdditiveGaussianNoiseImageFilter.hxx"
#endif
#endif
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