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 *
 *  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 itkFFTNormalizedCorrelationImageFilter_h
#define itkFFTNormalizedCorrelationImageFilter_h

#include "itkMaskedFFTNormalizedCorrelationImageFilter.h"

namespace itk
{
/**
 * \class FFTNormalizedCorrelationImageFilter
 * \brief Calculate normalized cross correlation using FFTs.
 *
 * This filter calculates the normalized cross correlation (NCC) of two
 * images using FFTs instead of spatial correlation.
 * It is much faster than spatial correlation
 * for reasonably large structuring elements.
 * This filter is a subclass of the more general
 * MaskedFFTNormalizedCorrelationImageFilter and operates by
 * essentially setting the masks in that algorithm to images of ones.
 * As described in detail in the references below, there is no computational
 * overhead to utilizing the more general masked algorithm because the FFTs
 * of the images of ones are still necessary for the computations.
 *
 * Inputs:
 * Two images are required as inputs, fixedImage and movingImage.
 * In the context of correlation, inputs are often defined as: "image"
 * and "template".  In this filter, the fixedImage plays the role of the
 * image, and the movingImage plays the role of the template.
 * However, this filter is capable of correlating any two images and
 * is not restricted to small movingImages (templates).
 *
 * Optional parameters:
 * The RequiredNumberOfOverlappingPixels enables the user to specify how many voxels
 * of the two images must overlap; any location in the correlation map that results
 * from fewer than this number of voxels will be set to zero.
 * Larger values zero-out pixels on a larger border around the correlation image.
 * Thus, larger values remove less stable computations but also limit the capture range.
 * If RequiredNumberOfOverlappingPixels is set to 0, the default, no zeroing will take place.
 *
 * Image size:
 * fixedImage and movingImage need not be the same size.
 * Furthermore, whereas some algorithms require that the "template"
 * be smaller than the "image" because of errors in the regions where
 * the two are not fully overlapping, this filter has no such restriction.
 *
 * Image spacing:
 * Since the computations are done in the pixel domain, all input
 * images must have the same spacing.
 *
 * Outputs;
 * The output is an image of RealPixelType that is the NCC of
 * the two images and its values range from -1.0 to 1.0.
 * The size of this NCC image is, by definition,
 * size(fixedImage) + size(movingImage) - 1.
 *
 * Example filter usage:
   \code
   using FilterType = itk::FFTNormalizedCorrelationImageFilter< ShortImageType, DoubleImageType >;
   FilterType::Pointer filter = FilterType::New();
   filter->SetFixedImage( fixedImage );
   filter->SetMovingImage( movingImage );
   filter->SetRequiredNumberOfOverlappingPixels(20);
   filter->Update();
   \endcode
 *
 * \warning The pixel type of the output image must be of real type
 * (float or double). ConceptChecking is used to enforce the output pixel
 * type. You will get a compilation error if the pixel type of the
 * output image is not float or double.
 *
 * References:
 * 1) D. Padfield. "Masked object registration in the Fourier domain."
 * Transactions on Image Processing.
 * 2) D. Padfield. "Masked FFT registration". In Proc. Computer
 * Vision and Pattern Recognition, 2010.
 *
 * \author: Dirk Padfield, GE Global Research, padfield\@research.ge.com
 * \ingroup ITKConvolution
 */

template <typename TInputImage, typename TOutputImage >
class ITK_TEMPLATE_EXPORT FFTNormalizedCorrelationImageFilter :
    public MaskedFFTNormalizedCorrelationImageFilter< TInputImage, TOutputImage >
{
public:
  ITK_DISALLOW_COPY_AND_ASSIGN(FFTNormalizedCorrelationImageFilter);

  /** Standard class type aliases. */
  using Self = FFTNormalizedCorrelationImageFilter;
  using Superclass = MaskedFFTNormalizedCorrelationImageFilter < TInputImage, TOutputImage >;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;

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

  /** Run-time type information (and related methods). */
  itkTypeMacro(FFTNormalizedCorrelationImageFilter, MaskedFFTNormalizedCorrelationImageFilter);

  /** Extract some information from the image types.  Dimensionality
   * of the two images is assumed to be the same. */
  static constexpr unsigned int ImageDimension = TOutputImage::ImageDimension;

  /** Extract some information from the image types. */
   using InputImageType = TInputImage;
   using OutputImageType = TOutputImage;
   using InputRegionType = typename InputImageType::RegionType;
   using InputImagePointer = typename InputImageType::Pointer;
   using InputImageConstPointer = typename InputImageType::ConstPointer;
   using InputSizeType = typename InputImageType::SizeType;
   using OutputImagePointer = typename OutputImageType::Pointer;
   using OutputPixelType = typename OutputImageType::PixelType;

protected:
  FFTNormalizedCorrelationImageFilter()
    {
      Self::RemoveInput("MovingImageMask");
      Self::RemoveInput("FixedImageMask");
    }
  ~FFTNormalizedCorrelationImageFilter() override = default;
  void PrintSelf(std::ostream& os, Indent indent) const override;

  /** Standard pipeline method.*/
  void GenerateData() override;

private:
  // Member variables.
};
} // end namespace itk

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

#endif
