DOC: fix typos in Modules/Filtering

Found via `codespell -q 3 -S ./Modules/ThirdParty,./Documentation/ReleaseNotes -L ans,ba,boun,childrens,developpement,dum,fiter,inout,ist,nd,normaly,numer,ot,positionn,pullrequest,reson,serie,te,unser`

Signed-off-by: luz paz <luzpaz@github.com>

Modules/Filtering/AntiAlias/test/itkAntiAliasBinaryImageFilterTest.cxx

@@ -122,7 +122,7 @@ itkAntiAliasBinaryImageFilterTest(int argc, char * argv[])
   antialiaser->GetMaximumRMSError();
 
 
-  // Generally a good idea to set this value as a safeguard against infinte
+  // Generally a good idea to set this value as a safeguard against infinite
   // loops if the MaximumRMSError has been set too low.
   antialiaser->SetNumberOfIterations(100);
 

Modules/Filtering/BiasCorrection/include/itkMRASlabIdentifier.h

@@ -117,7 +117,7 @@ class ITK_TEMPLATE_EXPORT MRASlabIdentifier : public Object
   itkSetMacro(SlicingDirection, int);
   itkGetConstReferenceMacro(SlicingDirection, int);
 
-  /** Compute the average values of mininum intensity pixels for each slice and
+  /** Compute the average values of minimum intensity pixels for each slice and
    * compare the average values with overall averages. */
   void
   GenerateSlabRegions();

Modules/Filtering/BiasCorrection/test/itkMRIBiasFieldCorrectionFilterTest.cxx

@@ -86,7 +86,7 @@ itkMRIBiasFieldCorrectionFilterTest(int, char *[])
   classSigmas[0] = 10.0;
   classSigmas[1] = 20.0;
 
-  // creats a normal random variate generator
+  // creates a normal random variate generator
   itk::Statistics::MersenneTwisterRandomVariateGenerator::Pointer randomGenerator =
     itk::Statistics::MersenneTwisterRandomVariateGenerator::New();
 

Modules/Filtering/BiasCorrection/test/itkN4BiasFieldCorrectionImageFilterTest.cxx

@@ -337,7 +337,7 @@ itkN4BiasFieldCorrectionImageFilterTest(int argc, char * argv[])
     return EXIT_FAILURE;
   }
 
-  // Exercise the objet's basic methods outside the templated test helper to
+  // Exercise the object's basic methods outside the templated test helper to
   // avoid the Superclass name not being found.
   constexpr unsigned int ImageDimension = 2;
 

Modules/Filtering/BinaryMathematicalMorphology/include/itkBinaryThinningImageFilter.hxx

@@ -175,7 +175,7 @@ BinaryThinningImageFilter<TInputImage, TOutputImage>::ComputeThinImage()
           // seven 8-neighbors valued 1.  Having only one such
           // neighbor implies that p1 is the end point of a skeleton
           // stroke and obviously should not be deleted.  Deleting p1
-          // if it has seven such neighbos would cause erosion into a region.
+          // if it has seven such neighbors would cause erosion into a region.
           PixelType numberOfOnNeighbors = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
 
           if (numberOfOnNeighbors > 1 && numberOfOnNeighbors < 7)

Modules/Filtering/BinaryMathematicalMorphology/test/itkBinaryMorphologicalClosingImageFilterTest.cxx

@@ -58,7 +58,7 @@ itkBinaryMorphologicalClosingImageFilterTest(int argc, char * argv[])
   auto filter = FilterType::New();
   filter->SetInput(reader->GetOutput());
   filter->SetKernel(ball);
-  // test the default attribute values, and exercise the accesors
+  // test the default attribute values, and exercise the accessors
   if (!filter->GetSafeBorder())
   {
     std::cerr << "Wrong SafeBorder default value" << std::endl;

Modules/Filtering/Convolution/include/itkNormalizedCorrelationImageFilter.hxx

@@ -179,7 +179,7 @@ NormalizedCorrelationImageFilter<TInputImage, TMaskImage, TOutputImage, TOperato
         // Compute the normalized correlation at this pixel.  The
         // template has already been normalized to mean zero and norm 1.
         // This simplifies the calculation to being just the correlation
-        // of the image neighborhod with the template, normalized by a
+        // of the image neighborhood with the template, normalized by a
         // function of the image neighborhood.
         sum = 0.0;
         sumOfSquares = 0.0;

Modules/Filtering/Convolution/test/itkFFTNormalizedCorrelationImageFilterTest.cxx

@@ -106,7 +106,7 @@ itkFFTNormalizedCorrelationImageFilterTest(int argc, char * argv[])
   }
   catch (const itk::ExceptionObject & excep)
   {
-    std::cerr << "Exception catched !" << std::endl;
+    std::cerr << "Exception caught !" << std::endl;
     std::cerr << excep << std::endl;
   }
 

Modules/Filtering/Convolution/test/itkMaskedFFTNormalizedCorrelationImageFilterTest.cxx

@@ -117,7 +117,7 @@ itkMaskedFFTNormalizedCorrelationImageFilterTest(int argc, char * argv[])
   }
   catch (const itk::ExceptionObject & excep)
   {
-    std::cerr << "Exception catched !" << std::endl;
+    std::cerr << "Exception caught !" << std::endl;
     std::cerr << excep << std::endl;
   }
 

Modules/Filtering/CurvatureFlow/include/itkCurvatureFlowFunction.hxx

@@ -97,7 +97,7 @@ CurvatureFlowFunction<TImage>::ComputeUpdate(const NeighborhoodType & it,
                          neighborhoodScales[i] * neighborhoodScales[j];
     }
 
-    // accumlate the gradient magnitude squared
+    // accumulate the gradient magnitude squared
     magnitudeSqr += itk::Math::sqr(static_cast<double>(firstderiv[i]));
   }
 
@@ -126,7 +126,7 @@ CurvatureFlowFunction<TImage>::ComputeUpdate(const NeighborhoodType & it,
     update += temp * itk::Math::sqr(static_cast<double>(firstderiv[i]));
   }
 
-  // accumlate -2 * dx * dy * dxy terms
+  // accumulate -2 * dx * dy * dxy terms
   for (i = 0; i < ImageDimension; ++i)
   {
     for (j = i + 1; j < ImageDimension; ++j)

Modules/Filtering/Deconvolution/include/itkLandweberDeconvolutionImageFilter.h

@@ -63,7 +63,7 @@ class ITK_TEMPLATE_EXPORT LandweberMethod
  * \brief Deconvolve an image using the Landweber deconvolution
  * algorithm.
  *
- * This filter implements the Landweber deconvolution algorthim as
+ * This filter implements the Landweber deconvolution algorithm as
  * defined in Bertero M and Boccacci P, "Introduction to Inverse
  * Problems in Imaging", 1998. The algorithm assumes that the input
  * image has been formed by a linear shift-invariant system with a

Modules/Filtering/DiffusionTensorImage/itk-module.cmake

@@ -1,4 +1,4 @@
-set(DOCUMENTATION "This module contains classes intended to generate or procees
+set(DOCUMENTATION "This module contains classes intended to generate or process
 diffusion tensor images. In particular you will find here the filter that
 computes a tensor image from a set of gradient images.")
 

Modules/Filtering/DisplacementField/include/itkDisplacementFieldTransform.hxx

@@ -49,7 +49,7 @@ DisplacementFieldTransform<TParametersValueType, VDimension>::DisplacementFieldT
   // Setup and assign parameter helper. This will hold the displacement field
   // for access through the common OptimizerParameters interface.
   auto * helper = new OptimizerParametersHelperType;
-  // After assigning this, m_Parametes will manage this,
+  // After assigning this, m_Parameters will manage this,
   // deleting when appropriate.
   this->m_Parameters.SetHelper(helper);
 

Modules/Filtering/DisplacementField/include/itkGaussianSmoothingOnUpdateDisplacementFieldTransform.h

@@ -28,7 +28,7 @@ namespace itk
 
 /** \class GaussianSmoothingOnUpdateDisplacementFieldTransform
  * \brief Modifies the UpdateTransformParameters method
- * to peform a Gaussian smoothing of the
+ * to perform a Gaussian smoothing of the
  * displacement field after adding the update array.
  *
  * This class is the same as \c DisplacementFieldTransform, except

Modules/Filtering/DisplacementField/include/itkGaussianSmoothingOnUpdateTimeVaryingVelocityFieldTransform.h

@@ -25,7 +25,7 @@ namespace itk
 
 /** \class GaussianSmoothingOnUpdateTimeVaryingVelocityFieldTransform
  * \brief Modifies the UpdateTransformParameters method
- * to peform a Gaussian smoothing of the
+ * to perform a Gaussian smoothing of the
  * velocity field after adding the update array.
  *
  * This class is the same as \c TimeVaryingVelocityFieldTransform, except

Modules/Filtering/DisplacementField/test/itkDisplacementFieldTransformCloneTest.cxx

@@ -109,7 +109,7 @@ itkDisplacementFieldTransformCloneTest(int, char *[])
   if (!originalIt.IsAtEnd() || !cloneIt.IsAtEnd())
   {
     std::cerr << "Test failed!" << std::endl;
-    std::cerr << "Displacment field size mismatch" << std::endl;
+    std::cerr << "Displacement field size mismatch" << std::endl;
     return EXIT_FAILURE;
   }
 

Modules/Filtering/DisplacementField/test/itkGaussianExponentialDiffeomorphicTransformTest.cxx

@@ -82,7 +82,7 @@ itkGaussianExponentialDiffeomorphicTransformTest(int, char *[])
   // std::cout << "params *before* SmoothDisplacementFieldGauss: " << std::endl
   //          << params << std::endl;
   params = displacementTransform->GetParameters();
-  // std::cout << "field->GetPixelContainter *after* Smooth: "
+  // std::cout << "field->GetPixelContainer *after* Smooth: "
   //          << field->GetPixelContainer() << std::endl;
   /* We should see 0's on all boundaries from the smoothing routine */
   unsigned int linelength = dimLength * dimensions;

Modules/Filtering/DisplacementField/test/itkGaussianSmoothingOnUpdateDisplacementFieldTransformTest.cxx

@@ -77,7 +77,7 @@ itkGaussianSmoothingOnUpdateDisplacementFieldTransformTest(int, char *[])
   // std::cout << "params *before* SmoothDisplacementFieldGauss: " << std::endl
   //          << params << std::endl;
   params = displacementTransform->GetParameters();
-  // std::cout << "field->GetPixelContainter *after* Smooth: "
+  // std::cout << "field->GetPixelContainer *after* Smooth: "
   //          << field->GetPixelContainer() << std::endl;
   /* We should see 0's on all boundaries from the smoothing routine */
   unsigned int linelength = dimLength * dimensions;

Modules/Filtering/DisplacementField/test/itkInverseDisplacementFieldImageFilterTest.cxx

@@ -99,7 +99,7 @@ itkInverseDisplacementFieldImageFilterTest(int argc, char * argv[])
 
   // Since the tested transform is upsampling by a factor of two, the
   // size of the inverse field should be twice the size of the input
-  // field. All other geomtry parameters are the same.
+  // field. All other geometry parameters are the same.
   filter->SetOutputSpacing(spacing);
   ITK_TEST_SET_GET_VALUE(spacing, filter->GetOutputSpacing());
 

Modules/Filtering/DistanceMap/include/itkApproximateSignedDistanceMapImageFilter.h

@@ -43,7 +43,7 @@ namespace itk
  * resulting in completely incorrect (read: zero-valued) output.
  *
  * The distances computed by this filter are Chamfer distances, which are only
- * an approximation to Euclidian distances, and are not as exact approximations
+ * an approximation to Euclidean distances, and are not as exact approximations
  * as those calculated by the DanielssonDistanceMapImageFilter. On the other hand,
  * this filter is faster.
  *

Modules/Filtering/DistanceMap/include/itkIsoContourDistanceImageFilter.hxx

@@ -315,7 +315,7 @@ IsoContourDistanceImageFilter<TInputImage, TOutputImage>::ThreadedGenerateDataBa
     ComputeValue(inNeigIt, outNeigIt, center, stride);
 
     ++bandIt;
-  } // Band iteratior
+  } // Band iterator
 }
 
 template <typename TInputImage, typename TOutputImage>

Modules/Filtering/FFT/include/itkFFTImageFilterFactory.h

@@ -61,7 +61,7 @@ struct FFTImageFilterTraits
  *
  * FFTImageFilterFactory can be used for making an FFT implementation
  * class available through object factory initialization if the class
- * meets certain critera:
+ * meets certain criteria:
  * - the FFT implementation class must be able to be templated over
  *   the pattern
  *   <TInput<PixelType, Dimension>, TOutput<PixelType, Dimension>

Modules/Filtering/FFT/include/itkFFTWHalfHermitianToRealInverseFFTImageFilter.hxx

@@ -109,7 +109,7 @@ FFTWHalfHermitianToRealInverseFFTImageFilter<TInputImage, TOutputImage>::BeforeT
   {
     // complex<double> and double[2] types are compatible memory layouts.
     // The reinterpret_cast is used here to
-    // make the "C" fftw libary compatible with the c++ complex<double>.
+    // make the "C" fftw library compatible with the c++ complex<double>.
     std::copy_n(
       inputPtr->GetBufferPointer(), totalInputSize, reinterpret_cast<typename InputImageType::PixelType *>(in));
   }

Modules/Filtering/FFT/src/itkFFTWGlobalConfiguration.cxx

@@ -385,7 +385,7 @@ FFTWGlobalConfiguration ::FFTWGlobalConfiguration()
     }
     else
     {
-      // In the abscence of explicit specification, point to
+      // In the absence of explicit specification, point to
       // the DefaultFilenameGenerator for creating the name
       auto * DefaultFilenameGenerator = new HardwareWisdomFilenameGenerator;
       this->m_WisdomFilenameGenerator = DefaultFilenameGenerator;

Modules/Filtering/FastMarching/include/itkFastMarchingBase.hxx

@@ -106,7 +106,7 @@ FastMarchingBase<TInput, TOutput>::Initialize(OutputDomainType * oDomain)
   this->InitializeOutput(oDomain);
 
   // By setting the output domain to the stopping criterion, we enable funky
-  // criterion based on informations extracted from it
+  // criterion based on information extracted from it
   m_StoppingCriterion->SetDomain(oDomain);
 }
 // -----------------------------------------------------------------------------

Modules/Filtering/FastMarching/include/itkFastMarchingUpwindGradientImageFilter.h

@@ -271,7 +271,7 @@ class ITK_TEMPLATE_EXPORT FastMarchingUpwindGradientImageFilter : public FastMar
       SizeValueType availableNumberOfTargets = m_TargetPoints->Size();
       if (targetModeMinPoints > availableNumberOfTargets)
       {
-        itkExceptionMacro(<< "Not enought target points: Available: " << availableNumberOfTargets
+        itkExceptionMacro(<< "Not enough target points: Available: " << availableNumberOfTargets
                           << "; Requested: " << targetModeMinPoints);
       }
     }

Modules/Filtering/FastMarching/test/itkFastMarchingImageFilterBaseTest.cxx

@@ -25,7 +25,7 @@
  * and does not exercise the base class filter. The process of testing
  * the running of the filter is delegated to other tests.
  * @tparam VDimension
- * @return EXIT_SUCCESS if all test passs, EXIT_FAILURE otherwise
+ * @return EXIT_SUCCESS if all test pass, EXIT_FAILURE otherwise
  */
 template <unsigned int VDimension>
 static int

Modules/Filtering/ImageCompose/include/itkJoinSeriesImageFilter.h

@@ -33,7 +33,7 @@ namespace itk
  * the size of the N+1'th dimension of the output is same as the number of
  * the inputs. The spacing and the origin (where the first input is placed)
  * for the N+1'th dimension is specified in this filter. The output image
- * informations for the first N dimensions are taken from the first input.
+ * information for the first N dimensions are taken from the first input.
  * Note that all the inputs should have the same information.
  *
  * \ingroup GeometricTransform

Modules/Filtering/ImageCompose/test/itkJoinSeriesImageFilterTest.cxx

@@ -161,7 +161,7 @@ itkJoinSeriesImageFilterTest(int, char *[])
   OutputImageType::Pointer output = streamingImage->GetOutput();
 
 
-  // Check the informations
+  // Check the information
   if (output->GetLargestPossibleRegion() != expectedRegion)
   {
     std::cout << "LargestPossibleRegion mismatch" << std::endl;

Modules/Filtering/ImageFeature/include/itkCannyEdgeDetectionImageFilter.hxx

@@ -214,7 +214,7 @@ CannyEdgeDetectionImageFilter<TInputImage, TOutputImage>::GenerateData()
   m_GaussianFilter->SetVariance(m_Variance);
   m_GaussianFilter->SetMaximumError(m_MaximumError);
   m_GaussianFilter->SetInput(input);
-  // Modify to force excution, due to grafting complications
+  // Modify to force execution, due to grafting complications
   m_GaussianFilter->Modified();
   m_GaussianFilter->Update();
   this->UpdateProgress(0.01f);

Modules/Filtering/ImageFeature/include/itkDiscreteGaussianDerivativeImageFilter.hxx

@@ -106,7 +106,7 @@ DiscreteGaussianDerivativeImageFilter<TInputImage, TOutputImage>::GenerateData()
   output->SetBufferedRegion(output->GetRequestedRegion());
   output->Allocate();
 
-  // Create an internal image to protect the input image's metdata
+  // Create an internal image to protect the input image's metadata
   // (e.g. RequestedRegion). The StreamingImageFilter changes the
   // requested region as poart of its normal provessing.
   auto localInput = TInputImage::New();

Modules/Filtering/ImageFeature/include/itkLaplacianRecursiveGaussianImageFilter.hxx

@@ -158,7 +158,7 @@ LaplacianRecursiveGaussianImageFilter<TInputImage, TOutputImage>::GenerateData()
   // initialize output image
   //
   // NOTE: We intentionally don't allocate the output image here,
-  // because the cast image filter will either run inplace, or alloate
+  // because the cast image filter will either run inplace, or allocate
   // the output there. The requested region has already been set in
   // ImageToImageFilter::GenerateInputImageFilter.
   typename TOutputImage::Pointer outputImage(this->GetOutput());

Modules/Filtering/ImageFeature/test/itkHessianToObjectnessMeasureImageFilterTest.cxx

@@ -50,7 +50,7 @@ itkHessianToObjectnessMeasureImageFilterTest(int argc, char * argv[])
 
   using HessianImageType = GaussianImageFilterType::OutputImageType;
 
-  // Delcare the type of objectness measure image filter
+  // Declare the type of objectness measure image filter
 
   using ObjectnessFilterType = itk::HessianToObjectnessMeasureImageFilter<HessianImageType, ImageType>;
 

Modules/Filtering/ImageFeature/test/itkHoughTransform2DCirclesImageTest.cxx

@@ -548,7 +548,7 @@ itkHoughTransform2DCirclesImageTest(int, char *[])
       std::cout << "Failure for circle #" << i << std::endl;
       std::cout << "Expected center: [" << center[i][0] << ", " << center[i][1] << "], found [" << centerResult[i][0]
                 << ", " << centerResult[i][1] << "]" << std::endl;
-      std::cout << "Excpected radius: " << radius[i] << ", found " << radiusResult[i] << std::endl;
+      std::cout << "Expected radius: " << radius[i] << ", found " << radiusResult[i] << std::endl;
       success = false;
     }
     else

Modules/Filtering/ImageFeature/test/itkHoughTransform2DLinesImageTest.cxx

@@ -23,7 +23,7 @@
 #include "itkTestingMacros.h"
 
 /**
- * This program looks for straight lines whithin an image
+ * This program looks for straight lines within an image
  * It uses the ITK HoughTransform2DLinesImageFilter.
  * - Read the image.
  * - Apply a gradient and thresholding functions.

Modules/Filtering/ImageFilterBase/include/itkMovingHistogramImageFilter.h

@@ -66,7 +66,7 @@ namespace itk
  * to consider that the histogram will never be empty.
  *
  * One histogram is created for each thread by the method NewHistogram().
- * The NewHistogram() method can be overriden to pass some parameters to the
+ * The NewHistogram() method can be overridden to pass some parameters to the
  * histogram.
  *
  * The neighborhood is defined by a structuring element, and must a

Modules/Filtering/ImageFilterBase/include/itkMovingHistogramImageFilterBase.h

@@ -69,7 +69,7 @@ namespace itk
  * to consider that the histogram will never be empty.
  *
  * One histogram is created for each thread by the method NewHistogram().
- * The NewHistogram() method can be overriden to pass some parameters to the
+ * The NewHistogram() method can be overridden to pass some parameters to the
  * histogram.
  *
  * The neighborhood is defined by a structuring element, and must a

Modules/Filtering/ImageFrequency/test/itkFrequencyBandImageFilterTest.cxx

@@ -97,7 +97,7 @@ itkFrequencyBandImageFilterTest(int argc, char * argv[])
   }
   else
   {
-    std::cerr << "Unkown string: " + evenOrOddInput + " . Use Even or Odd." << std::endl;
+    std::cerr << "Unknown string: " + evenOrOddInput + " . Use Even or Odd." << std::endl;
     return EXIT_FAILURE;
   }
 

Modules/Filtering/ImageFrequency/test/itkFrequencyIteratorsGTest.cxx

@@ -208,7 +208,7 @@ compareAllTypesOfIterators(typename TImageType::Pointer image, double difference
   // Compare full and hermitian
   // Hermitian saves memory, but at the cost of less precision
   // in the reconstruction (forward + inverse == original_image)
-  // This is the minimun threshold for the comparison between
+  // This is the minimum threshold for the comparison between
   // original and reconstructed image to be equal (without any extra band filter).
   bool fullAndHermitian = compareImages<ImageType>(filteredHermitianImage, filteredImage, differenceHermitianThreshold);
   EXPECT_TRUE(fullAndHermitian);

Modules/Filtering/ImageFusion/wrapping/CMakeLists.txt

@@ -1,6 +1,6 @@
 itk_wrap_module(ITKImageFusion)
 
-# Save default includes so they can be reseted afterwards
+# Save default includes so they can be reset afterwards
 set(tmp_default_includes ${WRAPPER_DEFAULT_INCLUDE})
 
 # Add itkStatisticsLabelObject.h, it is not automatically detected

Modules/Filtering/ImageGradient/test/itkVectorGradientMagnitudeImageFilterTest3.cxx

@@ -98,7 +98,7 @@ itkVectorGradientMagnitudeImageFilterTest3(int argc, char * argv[])
     return EXIT_FAILURE;
   }
 
-  // this verifies that the pipeline was executed as expected allong
+  // this verifies that the pipeline was executed as expected along
   // with correct region propagation and output information
   if (!monitor2->VerifyAllInputCanStream(4))
   {

Modules/Filtering/ImageGrid/include/itkBSplineResampleImageFilterBase.hxx

@@ -55,7 +55,7 @@ BSplineResampleImageFilterBase<TInputImage, TOutputImage>::PrintSelf(std::ostrea
 }
 
 /**
- * Intializes the Pyramid Spline Filter parameters for an "l2" filter
+ * Initializes the Pyramid Spline Filter parameters for an "l2" filter
  */
 template <typename TInputImage, typename TOutputImage>
 void

Modules/Filtering/ImageGrid/include/itkPermuteAxesImageFilter.h

@@ -29,7 +29,7 @@ namespace itk
  * PermuateAxesImageFilter permutes the image axes according to a
  * user specified order. The permutation order is set via method
  * SetOrder( order ) where the input is an array of ImageDimension
- * number of unsigned int. The elements of the array must be a rearrangment
+ * number of unsigned int. The elements of the array must be a rearrangement
  * of the numbers from 0 to ImageDimension - 1.
  *
  * The i-th axis of the output image corresponds with the order[i]-th