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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 itkCurvatureFlowImageFilter_h
#define itkCurvatureFlowImageFilter_h
#include "itkDenseFiniteDifferenceImageFilter.h"
#include "itkCurvatureFlowFunction.h"
namespace itk
{
/** \class CurvatureFlowImageFilter
* \brief Denoise an image using curvature driven flow.
*
* CurvatureFlowImageFilter implements a curvature driven image denoising
* algorithm. Iso-brightness contours in the grayscale input image are viewed
* as a level set. The level set is then evolved using a curvature-based speed
* function:
*
* \f[ I_t = \kappa |\nabla I| \f]
* where \f$ \kappa \f$ is the curvature.
*
* The advantage of this approach is that sharp boundaries are preserved
* with smoothing occurring only within a region. However, it should be
* noted that continuous application of this scheme will result in the
* eventual removal of all information as each contour shrinks to zero and
* disappear.
*
* Note that unlike level set segmentation algorithms,
* the image to be denoised is already the level set and can be set
* directly as the input using the SetInput() method.
*
* This filter has two parameters: the number of update iterations to
* be performed and the timestep between each update.
*
* The timestep should be "small enough" to ensure numerical stability.
* Stability is guarantee when the timestep meets the CFL
* (Courant-Friedrichs-Levy) condition. Broadly speaking, this condition
* ensures that each contour does not move more than one grid position
* at each timestep. In the literature, the timestep is typically user
* specified and have to manually tuned to the application.
*
* This filter make use of the multi-threaded finite difference solver
* hierarchy. Updates are computed using a CurvatureFlowFunction object. A
* zero flux Neumann boundary condition when computing derivatives near the
* data boundary.
*
* This filter may be streamed. To support streaming this filter produces a
* padded output which takes into account edge effects. The size of the
* padding is m_NumberOfIterations on each edge. Users of this filter should
* only make use of the center valid central region.
*
* \warning This filter assumes that the input and output types have the
* same dimensions. This filter also requires that the output image pixels
* are of a floating point type. This filter works for any dimensional images.
*
* Reference:
* "Level Set Methods and Fast Marching Methods", J.A. Sethian,
* Cambridge Press, Chapter 16, Second edition, 1999.
*
* \sa DenseFiniteDifferenceImageFilter
* \sa CurvatureFlowFunction
* \sa MinMaxCurvatureFlowImageFilter
* \sa BinaryMinMaxCurvatureFlowImageFilter
*
* \ingroup ImageEnhancement
* \ingroup MultiThreaded
* \ingroup Streamed
*
* Input/Output Restrictions:
* TInputImage and TOutputImage must have the same dimension.
* TOutputImage's pixel type must be a real number type.
* \ingroup ITKCurvatureFlow
*/
template< typename TInputImage, typename TOutputImage >
class ITK_TEMPLATE_EXPORT CurvatureFlowImageFilter:
public DenseFiniteDifferenceImageFilter< TInputImage, TOutputImage >
{
public:
/** Standard class typedefs. */
typedef CurvatureFlowImageFilter Self;
typedef DenseFiniteDifferenceImageFilter< TInputImage, TOutputImage > 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(CurvatureFlowImageFilter,
DenseFiniteDifferenceImageFilter);
/** InputImage type. */
typedef typename Superclass::InputImageType InputImageType;
/** OutputImage type. */
typedef typename Superclass::OutputImageType OutputImageType;
typedef typename OutputImageType::Pointer OutputImagePointer;
/** FiniteDifferenceFunction type. */
typedef typename Superclass::FiniteDifferenceFunctionType
FiniteDifferenceFunctionType;
/** CurvatureFlowFunction type. */
typedef CurvatureFlowFunction< OutputImageType >
CurvatureFlowFunctionType;
/** Dimensionality of input and output data is assumed to be the same.
* It is inherited from the superclass. */
itkStaticConstMacro(ImageDimension, unsigned int, Superclass::ImageDimension);
/** The pixel type of the output image will be used in computations.
* Inherited from the superclass. */
typedef typename Superclass::PixelType PixelType;
/** The time step type. Inherited from the superclass. */
typedef typename Superclass::TimeStepType TimeStepType;
/** Set the timestep parameter. */
itkSetMacro(TimeStep, TimeStepType);
/** Get the timestep parameter. */
itkGetConstMacro(TimeStep, TimeStepType);
#ifdef ITK_USE_CONCEPT_CHECKING
// Begin concept checking
itkConceptMacro( DoubleConvertibleToOutputCheck,
( Concept::Convertible< double, PixelType > ) );
itkConceptMacro( OutputConvertibleToDoubleCheck,
( Concept::Convertible< PixelType, double > ) );
itkConceptMacro( OutputDivisionOperatorsCheck,
( Concept::DivisionOperators< PixelType > ) );
itkConceptMacro( DoubleOutputMultiplyOperatorCheck,
( Concept::MultiplyOperator< double, PixelType, PixelType > ) );
itkConceptMacro( IntOutputMultiplyOperatorCheck,
( Concept::MultiplyOperator< int, PixelType, PixelType > ) );
itkConceptMacro( OutputLessThanDoubleCheck,
( Concept::LessThanComparable< PixelType, double > ) );
itkConceptMacro( OutputDoubleAdditiveOperatorsCheck,
( Concept::AdditiveOperators< PixelType, double > ) );
// End concept checking
#endif
protected:
CurvatureFlowImageFilter();
~CurvatureFlowImageFilter() ITK_OVERRIDE {}
void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
/** Supplies the halting criteria for this class of filters. The
* algorithm will stop after a user-specified number of iterations. */
virtual bool Halt() ITK_OVERRIDE
{
if ( this->GetElapsedIterations() == this->GetNumberOfIterations() )
{
return true;
}
else
{
return false;
}
}
/** Initialize the state of filter and equation before each iteration.
* Progress feeback is implemented as part of this method. */
virtual void InitializeIteration() ITK_OVERRIDE;
/** To support streaming, this filter produces a output which is
* larger than the original requested region. The output is padding
* by m_NumberOfIterations pixels on edge. */
virtual void EnlargeOutputRequestedRegion(DataObject *) ITK_OVERRIDE;
/** Edge effects are taken care of by padding the output requested
* region. As such, the input requested region needs to at
* minimum the same size as the output requested region. */
virtual void GenerateInputRequestedRegion() ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(CurvatureFlowImageFilter);
TimeStepType m_TimeStep;
};
} // end namspace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkCurvatureFlowImageFilter.hxx"
#endif
#endif
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