/usr/include/ITK-4.5/itkGPUGradientNDAnisotropicDiffusionFunction.h is in libinsighttoolkit4-dev 4.5.0-3.
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*
* Copyright Insight Software Consortium
*
* 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
*
* http://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 __itkGPUGradientNDAnisotropicDiffusionFunction_h
#define __itkGPUGradientNDAnisotropicDiffusionFunction_h
#include "itkGPUScalarAnisotropicDiffusionFunction.h"
#include "itkNeighborhoodAlgorithm.h"
#include "itkNeighborhoodInnerProduct.h"
#include "itkDerivativeOperator.h"
namespace itk
{
/** \class GPUGradientNDAnisotropicDiffusionFunction
*
* This class implements an N-dimensional version of the classic Perona-Malik
* anisotropic diffusion equation for scalar-valued images on the GPU. See
* itkAnisotropicDiffusionFunction for an overview of the anisotropic diffusion
* framework and equation.
*
* \par
* The conductance term for this implementation is chosen as a function of the
* gradient magnitude of the image at each point, reducing the strength of
* diffusion at edge pixels.
*
* \f[C(\mathbf{x}) = e^{-(\frac{\parallel \nabla U(\mathbf{x}) \parallel}{K})^2}\f].
*
* \par
* The numerical implementation of this equation is similar to that described
* in the Perona-Malik paper below, but uses a more robust technique
* for gradient magnitude estimation and has been generalized to N-dimensions.
*
* \par References
* Pietro Perona and Jalhandra Malik, ``Scale-space and edge detection using
* anisotropic diffusion,'' IEEE Transactions on Pattern Analysis Machine
* Intelligence, vol. 12, pp. 629-639, 1990.
*
* \ingroup ITKGPUAnisotropicSmoothing
*/
/** Create a helper GPU Kernel class for GPUGradientNDAnisotropicDiffusionFunction */
itkGPUKernelClassMacro(GPUGradientNDAnisotropicDiffusionFunctionKernel);
template< typename TImage >
class GPUGradientNDAnisotropicDiffusionFunction :
public GPUScalarAnisotropicDiffusionFunction< TImage >
{
public:
/** Standard class typedefs. */
typedef GPUGradientNDAnisotropicDiffusionFunction Self;
typedef GPUScalarAnisotropicDiffusionFunction< TImage > Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods) */
itkTypeMacro(GPUGradientNDAnisotropicDiffusionFunction,
GPUScalarAnisotropicDiffusionFunction);
/** Inherit some parameters from the superclass type. */
typedef typename Superclass::ImageType ImageType;
typedef typename Superclass::PixelType PixelType;
typedef typename Superclass::PixelRealType PixelRealType;
typedef typename Superclass::TimeStepType TimeStepType;
typedef typename Superclass::RadiusType RadiusType;
typedef typename Superclass::NeighborhoodType NeighborhoodType;
typedef typename Superclass::FloatOffsetType FloatOffsetType;
typedef SizeValueType NeighborhoodSizeValueType;
/** Inherit some parameters from the superclass type. */
itkStaticConstMacro(ImageDimension, unsigned int, Superclass::ImageDimension);
/** Get OpenCL Kernel source as a string, creates a GetOpenCLSource method */
itkGetOpenCLSourceFromKernelMacro(GPUGradientNDAnisotropicDiffusionFunctionKernel);
/** Compute the equation value. */
virtual void GPUComputeUpdate( const typename TImage::Pointer output, typename TImage::Pointer buffer,
void *globalData );
/** This method is called prior to each iteration of the solver. */
virtual void InitializeIteration()
{
m_K = static_cast< PixelType >( this->GetAverageGradientMagnitudeSquared()
* this->GetConductanceParameter() * this->GetConductanceParameter() * -2.0f );
}
protected:
GPUGradientNDAnisotropicDiffusionFunction();
~GPUGradientNDAnisotropicDiffusionFunction() {
}
/** Inner product function. */
NeighborhoodInnerProduct< ImageType > m_InnerProduct;
/** Slices for the ND neighborhood. */
std::slice x_slice[ImageDimension];
std::slice xa_slice[ImageDimension][ImageDimension];
std::slice xd_slice[ImageDimension][ImageDimension];
/** Derivative operator. */
DerivativeOperator< PixelType, itkGetStaticConstMacro(ImageDimension) > dx_op;
/** Modified global average gradient magnitude term. */
PixelType m_K;
NeighborhoodSizeValueType m_Center;
NeighborhoodSizeValueType m_Stride[ImageDimension];
static double m_MIN_NORM;
private:
GPUGradientNDAnisotropicDiffusionFunction(const Self &); //purposely not
// implemented
void operator=(const Self &); //purposely not
// implemented
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGPUGradientNDAnisotropicDiffusionFunction.hxx"
#endif
#endif
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