ITK  6.0.0
Insight Toolkit
Examples/Filtering/LaplacianRecursiveGaussianImageFilter2.cxx
/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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.
*
*=========================================================================*/
// Software Guide : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// ARGUMENTS: LaplacianRecursiveGaussianImageFilter2Output3.mha 3
// OUTPUTS: {LaplacianRecursiveGaussianImageFilter2Output3.png}
// Software Guide : EndCommandLineArgs
// Software Guide : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// ARGUMENTS: LaplacianRecursiveGaussianImageFilter2Output5.mha 5
// OUTPUTS: {LaplacianRecursiveGaussianImageFilter2Output5.png}
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// The previous example showed how to use the
// \doxygen{RecursiveGaussianImageFilter} for computing the equivalent of a
// Laplacian of an image after smoothing with a Gaussian. The elements used
// in this previous example have been packaged together in the
// \doxygen{LaplacianRecursiveGaussianImageFilter} in order to simplify its
// usage. This current example shows how to use this convenience filter for
// achieving the same results as the previous example.
//
// \index{itk::LaplacianRecursiveGaussianImageFilter}
//
// Software Guide : EndLatex
// Software Guide : BeginLatex
//
// The first step required to use this filter is to include its header file.
//
// \index{itk::LaplacianRecursiveGaussianImageFilter!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
int
main(int argc, char * argv[])
{
if (argc < 4)
{
std::cerr << "Usage: " << std::endl;
std::cerr
<< argv[0]
<< " inputImageFile outputImageFile sigma [RescaledOutputImageFile] "
<< std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// Types should be selected on the desired input and output pixel types.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using InputPixelType = float;
using OutputPixelType = float;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The input and output image types are instantiated using the pixel types.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using InputImageType = itk::Image<InputPixelType, 2>;
using OutputImageType = itk::Image<OutputPixelType, 2>;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The filter type is now instantiated using both the input image and the
// output image types.
//
// \index{itk::RecursiveGaussianImageFilter!Instantiation}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using FilterType =
OutputImageType>;
// Software Guide : EndCodeSnippet
auto reader = ReaderType::New();
reader->SetFileName(argv[1]);
// Software Guide : BeginLatex
//
// This filter packages all the components illustrated in the previous
// example. The filter is created by invoking the \code{New()} method and
// assigning the result to a \doxygen{SmartPointer}.
//
// \index{itk::LaplacianRecursiveGaussianImageFilter!New()}
// \index{itk::LaplacianRecursiveGaussianImageFilter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
auto laplacian = FilterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The option for normalizing across scale space can also be selected in
// this filter.
//
// \index{LaplacianRecursiveGaussianImageFilter!SetNormalizeAcrossScale()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
laplacian->SetNormalizeAcrossScale(false);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The input image can be obtained from the output of another
// filter. Here, an image reader is used as the source.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
laplacian->SetInput(reader->GetOutput());
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// It is now time to select the $\sigma$ of the Gaussian used to smooth the
// data. Note that $\sigma$ must be passed to both filters and that sigma
// is considered to be in millimeters. That is, at the moment of applying
// the smoothing process, the filter will take into account the spacing
// values defined in the image.
//
// \index{itk::LaplacianRecursiveGaussianImageFilter!SetSigma()}
// \index{SetSigma()!itk::LaplacianRecursiveGaussianImageFilter}
//
// Software Guide : EndLatex
const double sigma = std::stod(argv[3]);
// Software Guide : BeginCodeSnippet
laplacian->SetSigma(sigma);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Finally the pipeline is executed by invoking the \code{Update()} method.
//
// \index{itk::LaplacianRecursiveGaussianImageFilter!Update()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
try
{
laplacian->Update();
}
catch (const itk::ExceptionObject & err)
{
std::cout << "ExceptionObject caught !" << std::endl;
std::cout << err << std::endl;
return EXIT_FAILURE;
}
// Software Guide : EndCodeSnippet
// The image can also be saved into a file, by using the ImageFileWriter.
//
using WritePixelType = float;
using WriteImageType = itk::Image<WritePixelType, 2>;
auto writer = WriterType::New();
writer->SetInput(laplacian->GetOutput());
writer->SetFileName(argv[2]);
writer->Update();
// Rescale float outputs to png for inclusion in the Software guide
//
if (argc > 4)
{
using CharPixelType = unsigned char;
using CharImageType = itk::Image<CharPixelType, 2>;
using RescaleFilterType =
auto rescale = RescaleFilterType::New();
rescale->SetInput(laplacian->GetOutput());
rescale->SetOutputMinimum(0);
rescale->SetOutputMaximum(255);
using CharWriterType = itk::ImageFileWriter<CharImageType>;
auto charWriter = CharWriterType::New();
charWriter->SetFileName(argv[4]);
charWriter->SetInput(rescale->GetOutput());
charWriter->Update();
}
return EXIT_SUCCESS;
}
itk::LaplacianRecursiveGaussianImageFilter
Computes the Laplacian of Gaussian (LoG) of an image.
Definition: itkLaplacianRecursiveGaussianImageFilter.h:44
itkImageFileReader.h
itk::ImageFileReader
Data source that reads image data from a single file.
Definition: itkImageFileReader.h:75
itkLaplacianRecursiveGaussianImageFilter.h
itk::ImageFileWriter
Writes image data to a single file.
Definition: itkImageFileWriter.h:90
itkRescaleIntensityImageFilter.h
itkImageFileWriter.h
itk::RescaleIntensityImageFilter
Applies a linear transformation to the intensity levels of the input Image.
Definition: itkRescaleIntensityImageFilter.h:133
itk::Image
Templated n-dimensional image class.
Definition: itkImage.h:88
New
static Pointer New()