libinsighttoolkit3-dev 3.20.1-1 / usr / include / InsightToolkit / Review / itkOptBSplineInterpolateImageFunction.h

/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    itkOptBSplineInterpolateImageFunction.h
  Language:  C++
  Date:      $Date$
  Version:   $Revision$

  Copyright (c) Insight Software Consortium. All rights reserved.
  See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.

  Portions of this code are covered under the VTK copyright.
  See VTKCopyright.txt or http://www.kitware.com/VTKCopyright.htm for details.

     This software is distributed WITHOUT ANY WARRANTY; without even
     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
     PURPOSE.  See the above copyright notices for more information.

=========================================================================*/
#ifndef __itkOptBSplineInterpolateImageFunction_h
#define __itkOptBSplineInterpolateImageFunction_h

#include <vector>

#include "itkImageLinearIteratorWithIndex.h"
#include "itkInterpolateImageFunction.h"
#include "vnl/vnl_matrix.h"

#include "itkBSplineDecompositionImageFilter.h"
#include "itkConceptChecking.h"
#include "itkCovariantVector.h"

namespace itk
{
/** \class BSplineInterpolateImageFunction
 * \brief Evaluates the B-Spline interpolation of an image.  Spline order may be from 0 to 5.
 *
 * This class defines N-Dimension B-Spline transformation.
 * It is based on:
 *    [1] M. Unser,
 *       "Splines: A Perfect Fit for Signal and Image Processing,"
 *        IEEE Signal Processing Magazine, vol. 16, no. 6, pp. 22-38,
 *        November 1999.
 *    [2] M. Unser, A. Aldroubi and M. Eden,
 *        "B-Spline Signal Processing: Part I--Theory,"
 *        IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 821-832,
 *        February 1993.
 *    [3] M. Unser, A. Aldroubi and M. Eden,
 *        "B-Spline Signal Processing: Part II--Efficient Design and Applications,"
 *        IEEE Transactions on Signal Processing, vol. 41, no. 2, pp. 834-848,
 *        February 1993.
 * And code obtained from bigwww.epfl.ch by Philippe Thevenaz
 *
 * The B spline coefficients are calculated through the
 * BSplineDecompositionImageFilter
 *
 * Limitations:  Spline order must be between 0 and 5.
 *               Spline order must be set before setting the image.
 *               Uses mirror boundary conditions.
 *               Requires the same order of Spline for each dimension.
 *               Spline is determined in all dimensions, cannot selectively
 *                  pick dimension for calculating spline.
 *
 * \sa BSplineDecompositionImageFilter
 *
 * \ingroup ImageFunctions
 */
template <
  class TImageType,
  class TCoordRep = double,
  class TCoefficientType = double >
class ITK_EXPORT BSplineInterpolateImageFunction :
    public InterpolateImageFunction<TImageType,TCoordRep>
{
public:
  /** Standard class typedefs. */
  typedef BSplineInterpolateImageFunction                   Self;
  typedef InterpolateImageFunction<TImageType,TCoordRep>    Superclass;
  typedef SmartPointer<Self>                                Pointer;
  typedef SmartPointer<const Self>                          ConstPointer;

  /** Run-time type information (and related methods). */
  itkTypeMacro(BSplineInterpolateImageFunction, InterpolateImageFunction);


  /** New macro for creation of through a Smart Pointer */
  itkNewMacro( Self );

  /** OutputType typedef support. */
  typedef typename Superclass::OutputType OutputType;

  /** InputImageType typedef support. */
  typedef typename Superclass::InputImageType InputImageType;

  /** Dimension underlying input image. */
  itkStaticConstMacro(ImageDimension, unsigned int,Superclass::ImageDimension);

  /** Index typedef support. */
  typedef typename Superclass::IndexType IndexType;

  /** ContinuousIndex typedef support. */
  typedef typename Superclass::ContinuousIndexType ContinuousIndexType;

  /** PointType typedef support */
  typedef typename Superclass::PointType PointType;

  /** Iterator typedef support */
  typedef ImageLinearIteratorWithIndex<TImageType> Iterator;

  /** Internal Coefficient typedef support */
  typedef TCoefficientType CoefficientDataType;
  typedef Image<CoefficientDataType,
                     itkGetStaticConstMacro(ImageDimension) >
                                                           CoefficientImageType;

  /** Define filter for calculating the BSpline coefficients */
  typedef BSplineDecompositionImageFilter<TImageType,
                                               CoefficientImageType>
                                                              CoefficientFilter;
  typedef typename CoefficientFilter::Pointer CoefficientFilterPointer;

  /** Derivative typedef support */
  typedef CovariantVector<OutputType,
                          itkGetStaticConstMacro(ImageDimension) >
                                                            CovariantVectorType;


  /** Evaluate the function at a ContinuousIndex position.
   *
   * Returns the B-Spline interpolated image intensity at a
   * specified point position. No bounds checking is done.
   * The point is assume to lie within the image buffer.
   *
   * ImageFunction::IsInsideBuffer() can be used to check bounds before
   * calling the method. */
  virtual OutputType Evaluate( const PointType & point ) const
    {
    ContinuousIndexType index;
    this->GetInputImage()->TransformPhysicalPointToContinuousIndex( point,
                                                                    index );
    // No thread info passed in, so call method that doesn't need thread ID.
    return ( this->EvaluateAtContinuousIndex( index ) );
    }

  virtual OutputType Evaluate( const PointType & point,
                               unsigned int threadID ) const
    {
    ContinuousIndexType index;
    this->GetInputImage()->TransformPhysicalPointToContinuousIndex( point,
                                                                    index );
    return ( this->EvaluateAtContinuousIndex( index, threadID ) );
    }

  virtual OutputType EvaluateAtContinuousIndex( const ContinuousIndexType &
                                                                 index ) const
    {
    // Don't know thread information, make evaluateIndex, weights on the stack.
    // Slower, but safer.
    vnl_matrix<long>        evaluateIndex(ImageDimension, ( m_SplineOrder + 1 ));
    vnl_matrix<double>      weights(ImageDimension, ( m_SplineOrder + 1 ));

    // Pass evaluateIndex, weights by reference. They're only good as long
    // as this method is in scope.
    return this->EvaluateAtContinuousIndexInternal( index,
                                                    evaluateIndex,
                                                    weights);
    }

  virtual OutputType EvaluateAtContinuousIndex( const ContinuousIndexType &
                                                                        index,
                                                unsigned int threadID ) const;

  CovariantVectorType EvaluateDerivative( const PointType & point ) const
    {
    ContinuousIndexType index;
    this->GetInputImage()->TransformPhysicalPointToContinuousIndex( point,
                                                                    index );
    // No thread info passed in, so call method that doesn't need thread ID.
    return ( this->EvaluateDerivativeAtContinuousIndex( index ) );
    }

  CovariantVectorType EvaluateDerivative( const PointType & point,
                                          unsigned int threadID ) const
    {
    ContinuousIndexType index;
    this->GetInputImage()->TransformPhysicalPointToContinuousIndex( point,
                                                                    index );
    return ( this->EvaluateDerivativeAtContinuousIndex( index, threadID ) );
    }

  CovariantVectorType EvaluateDerivativeAtContinuousIndex(
                                         const ContinuousIndexType & x ) const
    {
    // Don't know thread information, make evaluateIndex, weights, weightsDerivative
    // on the stack.
    // Slower, but safer.
    vnl_matrix<long>          evaluateIndex(ImageDimension, ( m_SplineOrder + 1 ));
    vnl_matrix<double>        weights(ImageDimension, ( m_SplineOrder + 1 ));
    vnl_matrix<double>        weightsDerivative(ImageDimension, ( m_SplineOrder + 1));

    // Pass evaluateIndex, weights, weightsDerivative by reference. They're only good
    // as long as this method is in scope.
    return this->EvaluateDerivativeAtContinuousIndexInternal( x,
                                                              evaluateIndex,
                                                              weights,
                                                              weightsDerivative );
    }

  CovariantVectorType EvaluateDerivativeAtContinuousIndex(
                                         const ContinuousIndexType & x,
                                         unsigned int threadID ) const;

  void EvaluateValueAndDerivative( const PointType & point,
                                   OutputType & value,
                                   CovariantVectorType & deriv ) const
    {
    ContinuousIndexType index;
    this->GetInputImage()->TransformPhysicalPointToContinuousIndex( point,
                                                                    index );

    // No thread info passed in, so call method that doesn't need thread ID.
    this->EvaluateValueAndDerivativeAtContinuousIndex( index,
                                                       value,
                                                       deriv );
    }

  void EvaluateValueAndDerivative( const PointType & point,
                                   OutputType & value,
                                   CovariantVectorType & deriv,
                                   unsigned int threadID ) const
    {
    ContinuousIndexType index;
    this->GetInputImage()->TransformPhysicalPointToContinuousIndex( point,
                                                                    index );
    this->EvaluateValueAndDerivativeAtContinuousIndex( index,
                                                       value,
                                                       deriv,
                                                       threadID );
    }

  void EvaluateValueAndDerivativeAtContinuousIndex(
                                                const ContinuousIndexType & x,
                                                OutputType & value,
                                                CovariantVectorType & deriv
                                                ) const
    {
    // Don't know thread information, make evaluateIndex, weights, weightsDerivative
    // on the stack.
    // Slower, but safer.
    vnl_matrix<long>          evaluateIndex(ImageDimension, ( m_SplineOrder + 1 ));
    vnl_matrix<double>        weights(ImageDimension, ( m_SplineOrder + 1 ));
    vnl_matrix<double>        weightsDerivative(ImageDimension, ( m_SplineOrder + 1));

    // Pass evaluateIndex, weights, weightsDerivative by reference. They're only good
    // as long as this method is in scope.
    this->EvaluateValueAndDerivativeAtContinuousIndexInternal(x,
                                                              value,
                                                              deriv,
                                                              evaluateIndex,
                                                              weights,
                                                              weightsDerivative );
    }

  void EvaluateValueAndDerivativeAtContinuousIndex(
                                                const ContinuousIndexType & x,
                                                OutputType & value,
                                                CovariantVectorType & deriv,
                                                unsigned int threadID ) const;


  /** Get/Sets the Spline Order, supports 0th - 5th order splines. The default
   *  is a 3rd order spline. */
  void SetSplineOrder(unsigned int SplineOrder);
  itkGetConstMacro(SplineOrder, int);

  void SetNumberOfThreads(unsigned int numThreads);
  itkGetConstMacro(NumberOfThreads, int);

  /** Set the input image.  This must be set by the user. */
  virtual void SetInputImage(const TImageType * inputData);


  /** The UseImageDirection flag determines whether image derivatives are
   * computed with respect to the image grid or with respect to the physical
   * space. When this flag is ON the derivatives are computed with respect to
   * the coodinate system of physical space. The difference is whether we take
   * into account the image Direction or not. The flag ON will take into
   * account the image direction and will result in an extra matrix
   * multiplication compared to the amount of computation performed when the
   * flag is OFF.
   * The default value of this flag is the same as the CMAKE option
   * ITK_IMAGE_BEHAVES_AS_ORIENTED_IMAGE (i.e ON by default when
   * ITK_IMAGE_BEHAVES_AS_ORIENTED_IMAGE is ON, and  OFF by default
   * when ITK_IMAGE_BEHAVES_AS_ORIENTED_IMAGE is OFF). */
  itkSetMacro( UseImageDirection, bool );
  itkGetConstMacro( UseImageDirection, bool );
  itkBooleanMacro( UseImageDirection );


protected:

  /** The following methods take working space (evaluateIndex, weights, weightsDerivative)
   *  that is managed by the caller. If threadID is known, the working variables are looked
   *  up in the thread indexed arrays. If threadID is not known, working variables are made
   *  on the stack and passed to these methods. The stack allocation should be ok since
   *  these methods do not store the working variables, i.e. they are not expected to
   *  be available beyond the scope of the function call.
   *
   *  This was done to allow for two types of re-entrancy. The first is when a threaded
   *  filter, e.g. InterpolateImagePointsFilter calls EvaluateAtContinuousIndex from multiple
   *  threads without passing a threadID. So, EvaluateAtContinuousIndex must be thread safe.
   *  This is handled with the stack-based allocation of the working space.
   *
   *  The second form of re-entrancy involves methods that call EvaluateAtContinuousIndex
   *  from multiple threads, but pass a threadID. In this case, we can gain a little efficiency
   *  (hopefully) by looking up pre-allocated working space in arrays that are indexed by thread.
   *  The efficiency gain is likely dependent on the size of the working variables, which are
   *  in-turn dependent on the dimensionality of the image and the order of the spline.
   */
  virtual OutputType EvaluateAtContinuousIndexInternal( const ContinuousIndexType & index,
                                                        vnl_matrix<long>& evaluateIndex,
                                                        vnl_matrix<double>& weights) const;

  virtual void EvaluateValueAndDerivativeAtContinuousIndexInternal( const ContinuousIndexType & x,
                                                       OutputType & value,
                                                       CovariantVectorType & derivativeValue,
                                                       vnl_matrix<long>& evaluateIndex,
                                                       vnl_matrix<double>& weights,
                                                       vnl_matrix<double>& weightsDerivative
                                                       ) const;

  virtual CovariantVectorType EvaluateDerivativeAtContinuousIndexInternal( const ContinuousIndexType & x,
                                                                           vnl_matrix<long>& evaluateIndex,
                                                                           vnl_matrix<double>& weights,
                                                                           vnl_matrix<double>& weightsDerivative
                                                                           ) const;


  BSplineInterpolateImageFunction();
  ~BSplineInterpolateImageFunction();
  void PrintSelf(std::ostream& os, Indent indent) const;

  // These are needed by the smoothing spline routine.
  // temp storage for processing of Coefficients
  std::vector<CoefficientDataType>    m_Scratch;
  // Image size
  typename TImageType::SizeType       m_DataLength;
  // User specified spline order (3rd or cubic is the default)
  unsigned int                        m_SplineOrder;

  // Spline coefficients
  typename CoefficientImageType::ConstPointer       m_Coefficients;

private:
  BSplineInterpolateImageFunction( const Self& ); //purposely not implemented
  void operator=( const Self& ); //purposely not implemented

  /** Determines the weights for interpolation of the value x */
  void SetInterpolationWeights( const ContinuousIndexType & x,
                                const vnl_matrix<long> & EvaluateIndex,
                                vnl_matrix<double> & weights,
                                unsigned int splineOrder ) const;

  /** Determines the weights for the derivative portion of the value x */
  void SetDerivativeWeights( const ContinuousIndexType & x,
                             const vnl_matrix<long> & EvaluateIndex,
                             vnl_matrix<double> & weights,
                             unsigned int splineOrder ) const;

  /** Precomputation for converting the 1D index of the interpolation
   *  neighborhood to an N-dimensional index. */
  void GeneratePointsToIndex(  );

  /** Determines the indicies to use give the splines region of support */
  void DetermineRegionOfSupport( vnl_matrix<long> & evaluateIndex,
                                 const ContinuousIndexType & x,
                                 unsigned int splineOrder ) const;

  /** Set the indicies in evaluateIndex at the boundaries based on mirror
    * boundary conditions. */
  void ApplyMirrorBoundaryConditions(vnl_matrix<long> & evaluateIndex,
                                     unsigned int splineOrder) const;


  Iterator                  m_CIterator;    // Iterator for traversing spline coefficients.
  unsigned long             m_MaxNumberInterpolationPoints; // number of neighborhood points used for interpolation
  std::vector<IndexType>    m_PointsToIndex;  // Preallocation of interpolation neighborhood indicies

  CoefficientFilterPointer     m_CoefficientFilter;

  // flag to take or not the image direction into account when computing the
  // derivatives.
  bool m_UseImageDirection;

  unsigned int         m_NumberOfThreads;
  vnl_matrix<long>   * m_ThreadedEvaluateIndex;
  vnl_matrix<double> * m_ThreadedWeights;
  vnl_matrix<double> * m_ThreadedWeightsDerivative;
};

} // namespace itk

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkOptBSplineInterpolateImageFunction.txx"
#endif

#endif