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

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: itkLaplacianSharpeningImageFilter.txx,v $
  Language:  C++
  Date:      $Date: 2006/01/11 19:43:31 $
  Version:   $Revision: 1.4 $

  Copyright (c) Insight Software Consortium. All rights reserved.
  See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.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 _itkLaplacianSharpeningImageFilter_txx
#define _itkLaplacianSharpeningImageFilter_txx
#include "itkLaplacianSharpeningImageFilter.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
LaplacianSharpeningImageFilter< 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 
LaplacianSharpeningImageFilter<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
LaplacianSharpeningImageFilter< 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;
    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
