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

  Program:   Advanced Normalization Tools

  Copyright (c) ConsortiumOfANTS. All rights reserved.
  See accompanying COPYING.txt or
 https://github.com/stnava/ANTs/blob/master/ANTSCopyright.txt 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 __itkOptimalSharpeningImageFilter_hxx
#define __itkOptimalSharpeningImageFilter_hxx

#include "itkNeighborhoodOperatorImageFilter.h"
#include "itkLaplacianOperator.h"
#include "itkZeroFluxNeumannBoundaryCondition.h"
#include "itkProgressAccumulator.h"
#include "itkMinimumMaximumImageCalculator.h"
#include "itkImageRegionIterator.h"

namespace itk
{
template <typename TInputImage, typename TOutputImage>
void
OptimalSharpeningImageFilter<TInputImage, TOutputImage>::PrintSelf(std::ostream & os, Indent indent) const
{
  Superclass::PrintSelf(os, indent);

  os << indent << "UseImageSpacing = " << m_UseImageSpacing << std::endl;
}

template <typename TInputImage, typename TOutputImage>
void
OptimalSharpeningImageFilter<TInputImage, TOutputImage>::GenerateInputRequestedRegion()
{
  // call the superclass' implementation of this method. this should
  // copy the output requested region to the input requested region
  Superclass::GenerateInputRequestedRegion();

  // get pointers to the input and output
  InputImagePointer inputPtr = const_cast<TInputImage *>(this->GetInput());

  if (!inputPtr)
  {
    return;
  }

  // Build an operator so that we can determine the kernel size
  LaplacianOperator<RealType, ImageDimension> oper;
  oper.CreateOperator();

  // get a copy of the input requested region (should equal the output
  // requested region)
  typename TInputImage::RegionType inputRequestedRegion;
  inputRequestedRegion = inputPtr->GetRequestedRegion();

  // pad the input requested region by the operator radius
  inputRequestedRegion.PadByRadius(oper.GetRadius());

  // crop the input requested region at the input's largest possible region
  if (inputRequestedRegion.Crop(inputPtr->GetLargestPossibleRegion()))
  {
    inputPtr->SetRequestedRegion(inputRequestedRegion);
    return;
  }
  else
  {
    // Couldn't crop the region (requested region is outside the largest
    // possible region).  Throw an exception.

    // store what we tried to request (prior to trying to crop)
    inputPtr->SetRequestedRegion(inputRequestedRegion);

    // build an exception
    InvalidRequestedRegionError e(__FILE__, __LINE__);
    e.SetLocation(ITK_LOCATION);
    e.SetDescription("Requested region is (at least partially) outside the largest possible region.");
    e.SetDataObject(inputPtr);
    throw e;
  }
}

template <typename TInputImage, typename TOutputImage>
void
OptimalSharpeningImageFilter<TInputImage, TOutputImage>::GenerateData()
{
  // Create the Laplacian operator
  LaplacianOperator<RealType, ImageDimension> oper;
  double                                      s[ImageDimension];
  for (unsigned i = 0; i < ImageDimension; i++)
  {
    if (this->GetInput()->GetSpacing()[i] == 0.0)
    {
      itkExceptionMacro(<< "Image spacing cannot be zero");
    }
    else
    {
      s[i] = 1.0 / this->GetInput()->GetSpacing()[i];
    }
  }
  oper.SetDerivativeScalings(s);
  oper.CreateOperator();

  // do calculations in floating point
  typedef Image<RealType, ImageDimension>                                RealImageType;
  typedef NeighborhoodOperatorImageFilter<InputImageType, RealImageType> NOIF;
  ZeroFluxNeumannBoundaryCondition<InputImageType>                       nbc;

  typename NOIF::Pointer filter = NOIF::New();
  filter->OverrideBoundaryCondition(static_cast<typename NOIF::ImageBoundaryConditionPointerType>(&nbc));

  // Create a process accumulator for tracking the progress of this minipipeline
  ProgressAccumulator::Pointer progress = ProgressAccumulator::New();
  progress->SetMiniPipelineFilter(this);

  // Register the filter with the with progress accumulator using
  // equal weight proportion
  progress->RegisterInternalFilter(filter, 0.8f);

  //
  // set up the mini-pipline
  //
  filter->SetOperator(oper);
  filter->SetInput(this->GetInput());
  filter->GetOutput()->SetRequestedRegion(this->GetOutput()->GetRequestedRegion());

  // execute the mini-pipeline
  filter->Update();

  // determine how the data will need to scaled to be properly combined
  typename MinimumMaximumImageCalculator<InputImageType>::Pointer inputCalculator =
    MinimumMaximumImageCalculator<InputImageType>::New();
  typename MinimumMaximumImageCalculator<RealImageType>::Pointer filteredCalculator =
    MinimumMaximumImageCalculator<RealImageType>::New();

  inputCalculator->SetImage(this->GetInput());
  inputCalculator->SetRegion(this->GetOutput()->GetRequestedRegion());
  inputCalculator->Compute();

  filteredCalculator->SetImage(filter->GetOutput());
  filteredCalculator->SetRegion(this->GetOutput()->GetRequestedRegion());
  filteredCalculator->Compute();

  RealType inputShift, inputScale, filteredShift, filteredScale;
  inputShift = static_cast<RealType>(inputCalculator->GetMinimum());
  inputScale =
    static_cast<RealType>(inputCalculator->GetMaximum()) - static_cast<RealType>(inputCalculator->GetMinimum());

  filteredShift = filteredCalculator->GetMinimum(); // no need to cast
  filteredScale = filteredCalculator->GetMaximum() - filteredCalculator->GetMinimum();

  ImageRegionIterator<RealImageType>       it(filter->GetOutput(), filter->GetOutput()->GetRequestedRegion());
  ImageRegionConstIterator<InputImageType> inIt(this->GetInput(), this->GetOutput()->GetRequestedRegion());

  // combine the input and laplacian images
  RealType value, invalue;
  RealType inputSum = 0.0;
  RealType enhancedSum = 0.0;
  while (!it.IsAtEnd())
  {
    value = it.Get(); // laplacian value

    // rescale to [0,1]
    value = (value - filteredShift) / filteredScale;

    // rescale to the input dynamic range
    value = value * inputScale + inputShift;

    // combine the input and laplacian image (note that we subtract
    // the laplacian due to the signs in our laplacian kernel).
    invalue = static_cast<RealType>(inIt.Get());
    value = invalue - value * this->m_SValue;
    it.Set(value);

    inputSum += invalue;
    enhancedSum += value;
    ++it;
    ++inIt;
  }

  RealType inputMean = inputSum / static_cast<RealType>(this->GetOutput()->GetRequestedRegion().GetNumberOfPixels());
  RealType enhancedMean =
    enhancedSum / static_cast<RealType>(this->GetOutput()->GetRequestedRegion().GetNumberOfPixels());

  // update progress
  this->UpdateProgress(0.9);

  // copy and cast the output
  typename TOutputImage::Pointer output = this->GetOutput();
  output->SetBufferedRegion(output->GetRequestedRegion());
  output->AllocateInitialized();

  RealType        inputMinimum = inputCalculator->GetMinimum();
  RealType        inputMaximum = inputCalculator->GetMaximum();
  OutputPixelType castInputMinimum = static_cast<OutputPixelType>(inputMinimum);
  OutputPixelType castInputMaximum = static_cast<OutputPixelType>(inputMaximum);

  ImageRegionIterator<OutputImageType> outIt =
    ImageRegionIterator<OutputImageType>(output, output->GetRequestedRegion());
  outIt.GoToBegin();
  it.GoToBegin();
  while (!outIt.IsAtEnd())
  {
    value = it.Get();

    // adjust value to make the mean intensities before and after match
    value = value - enhancedMean + inputMean;

    if (value < inputMinimum)
    {
      outIt.Set(castInputMinimum);
    }
    else if (value > inputMaximum)
    {
      outIt.Set(castInputMaximum);
    }
    else
    {
      outIt.Set(static_cast<OutputPixelType>(value));
    }

    ++outIt;
    ++it;
  }

  // update progress
  this->UpdateProgress(1.0);
}
} // end namespace itk

#endif
