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

  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 "itkOptimalSharpeningImageFilter.h"

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

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

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

template <class TInputImage, class TOutputImage>
void
OptimalSharpeningImageFilter<TInputImage, TOutputImage>
::GenerateInputRequestedRegion()
throw (InvalidRequestedRegionError)
{
  // 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 <class TInputImage, class 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->Allocate();

  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
