DOC: Add brief description to image filters

InsightSoftwareConsortium · Mar 10, 2020 · 8a0deec · 8a0deec
1 parent c4ec825
commit 8a0deec
Show file tree

Hide file tree

Showing 5 changed files with 18 additions and 17 deletions.
diff --git a/Modules/Filtering/AnisotropicSmoothing/include/itkCurvatureAnisotropicDiffusionImageFilter.h b/Modules/Filtering/AnisotropicSmoothing/include/itkCurvatureAnisotropicDiffusionImageFilter.h
@@ -25,11 +25,11 @@ namespace itk
 {
 /**
  * \class CurvatureAnisotropicDiffusionImageFilter
+ * \brief This filter performs anisotropic diffusion on a scalar
+ * itk::Image using the modified curvature diffusion equation (MCDE).
  *
- * This filter performs anisotropic diffusion on a scalar itk::Image using the
- * modified curvature diffusion equation (MCDE) implemented in
- * itkCurvatureNDAnisotropicDiffusionFunction.  For detailed information on
- * anisotropic diffusion and the MCDE see itkAnisotropicDiffusionFunction and
+ * For detailed information on anisotropic diffusion and the MCDE see
+ * itkAnisotropicDiffusionFunction and
  * itkCurvatureNDAnisotropicDiffusionFunction.
  *
  * \par Inputs and Outputs

diff --git a/Modules/Filtering/AnisotropicSmoothing/include/itkGradientAnisotropicDiffusionImageFilter.h b/Modules/Filtering/AnisotropicSmoothing/include/itkGradientAnisotropicDiffusionImageFilter.h
@@ -24,11 +24,12 @@
 namespace itk
 {
 /** \class GradientAnisotropicDiffusionImageFilter
+ * \brief This filter performs anisotropic diffusion on a scalar
+ * itk::Image using the classic Perona-Malik, gradient magnitude based
+ * equation.
  *
- * This filter performs anisotropic diffusion on a scalar itk::Image using the
- * classic Perona-Malik, gradient magnitude based equation implemented in
- * itkGradientNDAnisotropicDiffusionFunction.  For detailed information on
- * anisotropic diffusion, see itkAnisotropicDiffusionFunction and
+ * For detailed information on anisotropic diffusion, see
+ * itkAnisotropicDiffusionFunction and
  * itkGradientNDAnisotropicDiffusionFunction.
  *
  * \par Inputs and Outputs

diff --git a/Modules/Filtering/DistanceMap/include/itkDanielssonDistanceMapImageFilter.h b/Modules/Filtering/DistanceMap/include/itkDanielssonDistanceMapImageFilter.h
@@ -24,15 +24,14 @@
 namespace itk
 {
 /**
- *\class DanielssonDistanceMapImageFilter
+ * \class DanielssonDistanceMapImageFilter
+ * \brief This filter computes the distance map of the input image
+ * as an approximation with pixel accuracy to the Euclidean distance.
  *
  * \tparam TInputImage Input Image Type
  * \tparam TOutputImage Output Image Type
  * \tparam TVoronoiImage Voronoi Image Type. Note the default value is TInputImage.
  *
- * \brief This filter computes the distance map of the input image
- * as an approximation with pixel accuracy to the Euclidean distance.
- *
  * The input is assumed to contain numeric codes defining objects.
  * The filter will produce as output the following images:
  *

diff --git a/Modules/Filtering/DistanceMap/include/itkSignedDanielssonDistanceMapImageFilter.h b/Modules/Filtering/DistanceMap/include/itkSignedDanielssonDistanceMapImageFilter.h
@@ -49,14 +49,14 @@ class ITK_TEMPLATE_EXPORT InvertIntensityFunctor
 namespace itk
 {
 /**
- *\class SignedDanielssonDistanceMapImageFilter
+ * \class SignedDanielssonDistanceMapImageFilter
+ * \brief This filter computes the signed distance map of the input
+ * image as an approximation with pixel accuracy to the Euclidean
+ * distance.
  *
  * This class is parameterized over the type of the input image
  * and the type of the output image.
  *
- * This filter computes the distance map of the input image
- * as an approximation with pixel accuracy to the Euclidean distance.
- *
  * For purposes of evaluating the signed distance map, the input is assumed
  * to be binary composed of pixels with value 0 and non-zero.
  *

diff --git a/Modules/Filtering/ImageFeature/include/itkLaplacianImageFilter.h b/Modules/Filtering/ImageFeature/include/itkLaplacianImageFilter.h
@@ -24,8 +24,9 @@ namespace itk
 {
 /**
  * \class LaplacianImageFilter
+ * \brief This filter computes the Laplacian of a scalar-valued image.
  *
- * This filter computes the Laplacian of a scalar-valued image. The Laplacian
+ * The Laplacian
  * is an isotropic measure of the 2nd spatial derivative of an image. The
  * Laplacian of an image highlights regions of rapid intensity change and is
  * therefore often used for edge detection.  Often, the Laplacian is applied to