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Compute Local Noise in Image

Synopsis

Compute the local noise in an image.

Results

input.mhd

output.mhd

Code

C++

#include "itkImage.h"
#include "itkImageRegionIteratorWithIndex.h"
#include "itkNoiseImageFilter.h"
#include "itkImageFileWriter.h"

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

void
CreateImage(ImageType::Pointer image);

int
main(int itkNotUsed(argc), char * itkNotUsed(argv)[])
{
  auto image = ImageType::New();
  CreateImage(image);

  using NoiseImageFilterType = itk::NoiseImageFilter<ImageType, ImageType>;
  auto noiseImageFilter = NoiseImageFilterType::New();
  noiseImageFilter->SetInput(image);
  noiseImageFilter->SetRadius(1);
  noiseImageFilter->Update();

  itk::WriteImage(noiseImageFilter->GetOutput(), "output.mhd");

  return EXIT_SUCCESS;
}

void
CreateImage(ImageType::Pointer image)
{
  // Create an image that is mostly constant but has some different kinds of objects.
  ImageType::IndexType start{};

  auto size = ImageType::SizeType::Filled(100);

  ImageType::RegionType region(start, size);

  // Create a black image
  image->SetRegions(region);
  image->Allocate();
  image->FillBuffer(0);

  // Create a white square
  itk::ImageRegionIteratorWithIndex<ImageType> imageIterator(image, region);

  while (!imageIterator.IsAtEnd())
  {
    if (imageIterator.GetIndex()[0] > 50 && imageIterator.GetIndex()[0] < 70 && imageIterator.GetIndex()[1] > 50 &&
        imageIterator.GetIndex()[1] < 70)
    {
      imageIterator.Set(255);
    }
    ++imageIterator;
  }

  // Create a rogue white pixel
  auto pixel = ImageType::IndexType::Filled(20);
  image->SetPixel(pixel, 255);

  itk::WriteImage(image, "input.mhd");
}

Classes demonstrated

template<typename TInputImage, typename TOutputImage>
class NoiseImageFilter : public itk::BoxImageFilter<TInputImage, TOutputImage>

Calculate the local noise in an image.

Computes an image where a given pixel is the standard deviation of the pixels in a neighborhood about the corresponding input pixel. This serves as an estimate of the local noise (or texture) in an image. Currently, this noise estimate assume a piecewise constant image. This filter should be extended to fitting a (hyper) plane to the neighborhood and calculating the standard deviation of the residuals to this (hyper) plane.

See also

Image

See also

Neighborhood

See also

NeighborhoodOperator

See also

NeighborhoodIterator

ITK Sphinx Examples:

• All ITK Sphinx Examples

• Compute Local Noise In Image

See itk::NoiseImageFilter for additional documentation.