/*=========================================================================
 *
 *  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 itkNarrowBandThresholdSegmentationLevelSetImageFilter_h
#define itkNarrowBandThresholdSegmentationLevelSetImageFilter_h

#include "itkNarrowBandLevelSetImageFilter.h"
#include "itkThresholdSegmentationLevelSetFunction.h"

namespace itk
{
/** \class NarrowBandThresholdSegmentationLevelSetImageFilter
 *    \brief Segments structures in images based on intensity values.
 *
 *  \par IMPORTANT
 *  The SegmentationLevelSetImageFilter class and the
 *  ThresholdSegmentationLevelSetFunction class contain additional information
 *  necessary to the full understanding of how to use this filter.
 *
 *  \par OVERVIEW
 *  This class is a level set method segmentation filter.  It constructs a
 *  speed function which is close to zero at the upper and lower bounds of an
 *  intensity window, effectively locking the propagating front onto those
 *  edges.  Elsewhere, the front will propagate quickly.
 *
 *  \par INPUTS
 *  This filter requires two inputs.  The first input is a seed
 *  image.  This seed image must contain an isosurface that you want to use as the
 *  seed for your segmentation.  It can be a binary, graylevel, or floating
 *  point image.  The only requirement is that it contain a closed isosurface
 *  that you will identify as the seed by setting the IsosurfaceValue parameter
 *  of the filter.  For a binary image you will want to set your isosurface
 *  value halfway between your on and off values (i.e. for 0's and 1's, use an
 *  isosurface value of 0.5).
 *
 *  \par
 *  The second input is the feature image.  This is the image from which the
 *  speed function will be calculated.  For most applications, this is the
 *  image that you want to segment. The desired isosurface in your seed image
 *  should lie within the region of your feature image that you are trying to
 *  segment. Note that this filter does no preprocessing of the feature image
 *  before thresholding.
 *
 *  \par
 *  See SegmentationLevelSetImageFilter for more information on Inputs.
 *
 *  \par OUTPUTS
 *  The filter outputs a single, scalar, real-valued image.
 *  Positive values in the output image are inside the segmented region
 *  and negative values in the image are outside of the inside region.  The
 *  zero crossings of the image correspond to the position of the level set
 *  front.
 *
 *  \par
 * See SparseFieldLevelSetImageFilter and
 * SegmentationLevelSetImageFilter for more information.
 *
 * \par PARAMETERS
 * In addition to parameters described in SegmentationLevelSetImageFilter,
 * this filter adds the UpperThreshold and LowerThreshold.  See
 * ThresholdSegmentationLevelSetFunction for a description of how these values
 * affect the segmentation.
 *
 * \sa SegmentationLevelSetImageFilter
 * \sa ThresholdSegmentationLevelSetFunction,
 * \sa SparseFieldLevelSetImageFilter
 * \ingroup ITKLevelSets
 */
template <typename TInputImage, typename TFeatureImage, typename TOutputPixelType = float>
class ITK_TEMPLATE_EXPORT NarrowBandThresholdSegmentationLevelSetImageFilter
  : public NarrowBandLevelSetImageFilter<TInputImage,
                                         TFeatureImage,
                                         TOutputPixelType,
                                         Image<TOutputPixelType, TInputImage::ImageDimension>>
{
public:
  /** Standard class type aliases */
  using Self = NarrowBandThresholdSegmentationLevelSetImageFilter;
  using Superclass = NarrowBandLevelSetImageFilter<TInputImage,
                                                   TFeatureImage,
                                                   TOutputPixelType,
                                                   Image<TOutputPixelType, TInputImage::ImageDimension>>;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;

  /** Inherited type alias from the superclass. */
  using typename Superclass::ValueType;
  using typename Superclass::OutputImageType;
  using typename Superclass::FeatureImageType;

  /** Type of the segmentation function */
  using ThresholdFunctionType = ThresholdSegmentationLevelSetFunction<OutputImageType, FeatureImageType>;
  using ThresholdFunctionPointer = typename ThresholdFunctionType::Pointer;

  /** \see LightObject::GetNameOfClass() */
  itkOverrideGetNameOfClassMacro(NarrowBandThresholdSegmentationLevelSetImageFilter);

  /** Method for creation through the object factory */
  itkNewMacro(Self);

  /** Get/Set the threshold values that will be used to calculate the speed
    function. */
  void
  SetUpperThreshold(ValueType v)
  {
    this->m_ThresholdFunction->SetUpperThreshold(v);
    this->Modified();
  }

  void
  SetLowerThreshold(ValueType v)
  {
    this->m_ThresholdFunction->SetLowerThreshold(v);
    this->Modified();
  }

  ValueType
  GetUpperThreshold() const
  {
    return m_ThresholdFunction->GetUpperThreshold();
  }

  ValueType
  GetLowerThreshold() const
  {
    return m_ThresholdFunction->GetLowerThreshold();
  }

  /** Set/Get the weight applied to the edge (Laplacian) attractor in the speed
   *  term function. Zero will turn this term off. */
  void
  SetEdgeWeight(ValueType v)
  {
    this->m_ThresholdFunction->SetEdgeWeight(v);
    this->Modified();
  }

  ValueType
  GetEdgeWeight() const
  {
    return m_ThresholdFunction->GetEdgeWeight();
  }

  /** Anisotropic diffusion is applied to the FeatureImage before calculating
   * the Laplacian (edge) term. This method sets/gets the number of diffusion
   * iterations. */
  void
  SetSmoothingIterations(int v)
  {
    this->m_ThresholdFunction->SetSmoothingIterations(v);
    this->Modified();
  }

  int
  GetSmoothingIterations() const
  {
    return m_ThresholdFunction->GetSmoothingIterations();
  }

  /** Anisotropic diffusion is applied to the FeatureImage before calculating
   * the Laplacian (edge) term. This method sets/gets the diffusion time
   * step. */
  void
  SetSmoothingTimeStep(ValueType v)
  {
    this->m_ThresholdFunction->SetSmoothingTimeStep(v);
    this->Modified();
  }

  ValueType
  GetSmoothingTimeStep() const
  {
    return m_ThresholdFunction->GetSmoothingTimeStep();
  }

  /** Anisotropic diffusion is applied to the FeatureImage before calculating
   * the Laplacian (edge) term. This method sets/gets the smoothing
   * conductance. */
  void
  SetSmoothingConductance(ValueType v)
  {
    this->m_ThresholdFunction->SetSmoothingConductance(v);
    this->Modified();
  }

  ValueType
  GetSmoothingConductance() const
  {
    return m_ThresholdFunction->GetSmoothingConductance();
  }

#ifdef ITK_USE_CONCEPT_CHECKING
  // Begin concept checking
  itkConceptMacro(OutputHasNumericTraitsCheck, (Concept::HasNumericTraits<TOutputPixelType>));
  // End concept checking
#endif

protected:
  ~NarrowBandThresholdSegmentationLevelSetImageFilter() override = default;
  NarrowBandThresholdSegmentationLevelSetImageFilter();

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

  NarrowBandThresholdSegmentationLevelSetImageFilter(const Self &); // purposely
                                                                    // not impl.
  void
  operator=(const Self &); // purposely
                           // not
                           // implemented

private:
  ThresholdFunctionPointer m_ThresholdFunction{};
};
} // end namespace itk

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

#endif
