/*=========================================================================
 *
 *  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 itkGaussianOperator_h
#define itkGaussianOperator_h

#include "itkNeighborhoodOperator.h"
#include <cmath>
namespace itk
{
/**
 * \class GaussianOperator
 * \brief A NeighborhoodOperator whose coefficients are a one
 * dimensional, discrete Gaussian kernel.
 *
 * GaussianOperator can be used to perform Gaussian blurring
 * by taking its inner product with to a Neighborhood
 * (NeighborhooIterator) that is swept across an image region.
 * It is a directional operator.  N successive applications
 * oriented along each dimensional direction will effect separable,
 * efficient, N-D Gaussian blurring of an image region.
 *
 * GaussianOperator takes two parameters:
 *
 * (1) The floating-point variance of the desired Gaussian function.
 *
 * (2) The "maximum error" allowed in the discrete Gaussian
 * function.  "Maximum errror" is defined as the difference between the area
 * under the discrete Gaussian curve and the area under the continuous
 * Gaussian. Maximum error affects the Gaussian operator size. Care should
 * be taken not to make this value too small relative to the variance
 * lest the operator size become unreasonably large.
 *
 * References:
 * The Gaussian kernel contained in this operator was described
 * by Tony Lindeberg (Discrete Scale-Space Theory and the Scale-Space
 * Primal Sketch.  Dissertation. Royal Institute of Technology, Stockholm,
 * Sweden. May 1991.).
 *
 * \sa NeighborhoodOperator
 * \sa NeighborhoodIterator
 * \sa Neighborhood
 *
 * \ingroup Operators
 * \ingroup ITKCommon
 *
 * \wiki
 * \wikiexample{Operators/GaussianOperator,Create a Gaussian kernel}
 * \endwiki
 */
template< typename TPixel, unsigned int VDimension = 2,
          typename TAllocator = NeighborhoodAllocator< TPixel > >
class GaussianOperator:
  public NeighborhoodOperator< TPixel, VDimension, TAllocator >
{
public:
  /** Standard class typedefs. */
  typedef GaussianOperator                                       Self;
  typedef NeighborhoodOperator< TPixel, VDimension, TAllocator > Superclass;

  itkTypeMacro(GaussianOperator, NeighborhoodOperator);

  /** Constructor. */
  GaussianOperator():m_Variance(1), m_MaximumError(.01), m_MaximumKernelWidth(30) {}

  /** Copy constructor */
  GaussianOperator(const Self & other):
    NeighborhoodOperator< TPixel, VDimension, TAllocator >(other)
  {
    m_Variance = other.m_Variance;
    m_MaximumError = other.m_MaximumError;
    m_MaximumKernelWidth = other.m_MaximumKernelWidth;
  }

  /** Assignment operator */
  Self & operator=(const Self & other)
  {
    if(this != &other)
      {
      Superclass::operator=(other);
      m_Variance = other.m_Variance;
      m_MaximumError = other.m_MaximumError;
      m_MaximumKernelWidth = other.m_MaximumKernelWidth;
      }
    return *this;
  }

  /** Sets the desired variance of the Gaussian kernel. */
  void SetVariance(const double & variance)
  {
    m_Variance = variance;
  }

  /** Sets the desired maximum error of the gaussian approximation.  Maximum
   * error is the difference between the area under the discrete Gaussian curve
   * and the area under the continuous Gaussian. Maximum error affects the
   * Gaussian operator size. The value must be between 0.0 and 1.0. */
  void SetMaximumError(const double & max_error)
  {
    if ( max_error >= 1 || max_error <= 0 )
      {
      itkExceptionMacro("Maximum Error Must be in the range [ 0.0 , 1.0 ]");
      }

    m_MaximumError = max_error;
  }

  /** Returns the variance of the Gaussian (scale) for the operator. */
  double GetVariance()
  {  return m_Variance;  }

  /** Returns the maximum error of the gaussian approximation.  Maximum error is
   * the difference between the area under the discrete Gaussian curve and the
   * area under the continuous Gaussian. Maximum error affects the Gaussian
   * operator size. */
  double GetMaximumError()
  {    return m_MaximumError;  }

  /** Sets a limit for growth of the kernel.  Small maximum error values with
   *  large variances will yield very large kernel sizes.  This value can be
   *  used to truncate a kernel in such instances.  A warning will be given on
   *  truncation of the kernel. */
  void SetMaximumKernelWidth(unsigned int n)
  {    m_MaximumKernelWidth = n; }

  /** Returns the maximum allowed kernel width. */
  unsigned int GetMaximumKernelWidth() const
  {   return m_MaximumKernelWidth; }

  /** Prints some debugging information. */
  virtual void PrintSelf(std::ostream & os, Indent i) const ITK_OVERRIDE
  {
    os << i << "GaussianOperator { this=" << this
       << ", m_Variance = " << m_Variance
       << ", m_MaximumError = " << m_MaximumError
       << "} "  << std::endl;
    Superclass::PrintSelf( os, i.GetNextIndent() );
  }

protected:
  typedef typename Superclass::CoefficientVector CoefficientVector;

public:
  /** Returns the value of the modified Bessel function I0(x) at a point x >= 0.
    */
  double ModifiedBesselI0(double);

  /** Returns the value of the modified Bessel function I1(x) at a point x,
   * x real.  */
  double ModifiedBesselI1(double);

  /** Returns the value of the modified Bessel function Ik(x) at a point x>=0,
   * where k>=2. */
  double ModifiedBesselI(int, double);

protected:
  /** Calculates operator coefficients. */
  CoefficientVector GenerateCoefficients() ITK_OVERRIDE;

  /** Arranges coefficients spatially in the memory buffer. */
  void Fill(const CoefficientVector & coeff) ITK_OVERRIDE
  {    this->FillCenteredDirectional(coeff);  }

private:
  /** Desired variance of the discrete Gaussian function. */
  double m_Variance;

  /** Difference between the areas under the curves of the continuous and
   * discrete Gaussian functions. */
  double m_MaximumError;

  /** Maximum kernel size allowed.  This value is used to truncate a kernel
   *  that has grown too large.  A warning is given when the specified maximum
   *  error causes the kernel to exceed this size. */
  unsigned int m_MaximumKernelWidth;

};
} // namespace itk

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGaussianOperator.hxx"
#endif

#endif
