Scale All Pixel’s Sum to Constant

Synopsis

Scale all pixels so that their sum is a specified constant.

Results

Output:

0.111111
0.111111
0.111111
0.111111
0.111111
0.111111
0.111111
0.111111
0.111111

Code

C++

#include "itkImage.h"
#include "itkImageRegionConstIterator.h"
#include "itkNormalizeToConstantImageFilter.h"

using ImageType = itk::Image<float, 2>;

static void
CreateImage(ImageType::Pointer image);

int
main(int, char *[])
{
  // Create an image
  ImageType::Pointer image = ImageType::New();
  CreateImage(image);

  using NormalizeToConstantImageFilterType = itk::NormalizeToConstantImageFilter<ImageType, ImageType>;
  NormalizeToConstantImageFilterType::Pointer normalizeToConstantImageFilter =
    NormalizeToConstantImageFilterType::New();
  normalizeToConstantImageFilter->SetInput(image);
  normalizeToConstantImageFilter->SetConstant(1);
  normalizeToConstantImageFilter->Update();

  itk::ImageRegionConstIterator<ImageType> imageIterator(
    normalizeToConstantImageFilter->GetOutput(),
    normalizeToConstantImageFilter->GetOutput()->GetLargestPossibleRegion());

  // The output pixels should all be 1/9 (=0.11111)
  while (!imageIterator.IsAtEnd())
  {
    std::cout << imageIterator.Get() << std::endl;
    ++imageIterator;
  }

  return EXIT_SUCCESS;
}

static void
CreateImage(ImageType::Pointer image)
{
  // Create an image full of 1's

  ImageType::IndexType start;
  start.Fill(0);

  ImageType::SizeType size;
  size.Fill(3);

  ImageType::RegionType region(start, size);

  image->SetRegions(region);
  image->Allocate();
  image->FillBuffer(1);
}

Classes demonstrated

template<typename TInputImage, typename TOutputImage>
class NormalizeToConstantImageFilter : public itk::ImageToImageFilter<TInputImage, TOutputImage>

Scales image pixel intensities to make the sum of all pixels equal a user-defined constant.

The default value of the constant is 1. It can be changed with SetConstant().

This transform is especially useful for normalizing a convolution kernel.

This code was contributed in the Insight Journal paper: “FFT based

convolution” by Lehmann G.

http://insight-journal.org/browse/publication/717

Author

Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA de Jouy-en-Josas, France.

See

NormalizeImageFilter

See

StatisticsImageFilter

See

DivideImageFilter

ITK Sphinx Examples:

See itk::NormalizeToConstantImageFilter for additional documentation.