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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 "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;
  start.Fill(0);

  ImageType::SizeType size;
  size.Fill(100);

  ImageType::RegionType region(start, size);

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

  // Create a white square
  itk::ImageRegionIterator<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
  ImageType::IndexType pixel;
  pixel.Fill(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

Image

See

Neighborhood

See

NeighborhoodOperator

See

NeighborhoodIterator

ITK Sphinx Examples:

• All ITK Sphinx Examples

• Compute Local Noise In Image

See itk::NoiseImageFilter for additional documentation.