Compute Gradient Magnitude Recursive Gaussian of Grayscale Image#

Synopsis#

Compute the gradient magnitude of the image after first smoothing with a Gaussian kernel.

Results#

Code#

Python#

#!/usr/bin/env python

import itk
import argparse

parser = argparse.ArgumentParser(
    description="Compute Gradient Magnitude Recursive Gaussian."
)
parser.add_argument("input_image")
parser.add_argument("output_image")
parser.add_argument("sigma")
args = parser.parse_args()

PixelType = itk.F
Dimension = 2
ImageType = itk.Image[PixelType, Dimension]

reader = itk.ImageFileReader[ImageType].New()
reader.SetFileName(args.input_image)

gradientMagnitudeImageFilter = itk.GradientMagnitudeRecursiveGaussianImageFilter.New(
    reader
)
gradientMagnitudeImageFilter.SetInput(reader.GetOutput())
gradientMagnitudeImageFilter.SetSigma(args.sigma)

writer = itk.ImageFileWriter[ImageType].New()
writer.SetFileName(args.output_image)
writer.SetInput(gradientMagnitudeImageFilter.GetOutput())

writer.Update()

C++#

#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkGradientMagnitudeRecursiveGaussianImageFilter.h"

int
main(int argc, char * argv[])
{
  if (argc != 4)
  {
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0];
    std::cerr << "<InputFileName> <OutputFileName> <Sigma>";
    std::cerr << std::endl;
    return EXIT_FAILURE;
  }
  const char * inputImage = argv[1];
  const char * outputImage = argv[2];
  const double sigma = std::stod(argv[3]);

  constexpr unsigned int Dimension = 2;
  using PixelType = float;
  using ImageType = itk::Image<PixelType, Dimension>;

  const auto input = itk::ReadImage<ImageType>(inputImage);

  using FilterType = itk::GradientMagnitudeRecursiveGaussianImageFilter<ImageType, ImageType>;
  auto filter = FilterType::New();
  filter->SetInput(input);
  filter->SetSigma(sigma);

  try
  {
    itk::WriteImage(filter->GetOutput(), outputImage);
  }
  catch (const itk::ExceptionObject & error)
  {
    std::cerr << "Error: " << error << std::endl;
    return EXIT_FAILURE;
  }

  return EXIT_SUCCESS;
}

Classes demonstrated#

template<typename TInputImage, typename TOutputImage = TInputImage> class GradientMagnitudeRecursiveGaussianImageFilter : public itk::InPlaceImageFilter<TInputImage, TOutputImage>

Computes the Magnitude of the Gradient of an image by convolution with the first derivative of a Gaussian.

This filter is implemented using the recursive gaussian filters

ITK Sphinx Examples:

All ITK Sphinx Examples

Compute Gradient Magnitude Of Grayscale Image

See itk::GradientMagnitudeRecursiveGaussianImageFilter for additional documentation.