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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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
*
* http://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.
*
*=========================================================================*/
#ifndef itkConvolutionImageFilter_hxx
#define itkConvolutionImageFilter_hxx
#include "itkConvolutionImageFilter.h"
#include "itkConstantPadImageFilter.h"
#include "itkCropImageFilter.h"
#include "itkFlipImageFilter.h"
#include "itkImageBase.h"
#include "itkImageKernelOperator.h"
#include "itkNeighborhoodOperatorImageFilter.h"
#include "itkNormalizeToConstantImageFilter.h"
namespace itk
{
template< typename TInputImage, typename TKernelImage, typename TOutputImage >
ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >
::ConvolutionImageFilter()
{
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage >
void
ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >
::GenerateData()
{
// Allocate the output
this->AllocateOutputs();
// Create a process accumulator for tracking the progress of this minipipeline
ProgressAccumulator::Pointer progress = ProgressAccumulator::New();
progress->SetMiniPipelineFilter( this );
// Build a mini-pipeline that involves a
// NeighborhoodOperatorImageFilter to compute the convolution, a
// normalization filter for the kernel, and a pad filter for making
// the kernel an odd size.
if ( this->GetNormalize() )
{
typedef typename NumericTraits< typename TKernelImage::PixelType >::RealType RealPixelType;
typedef Image< RealPixelType, ImageDimension > RealImageType;
typedef NormalizeToConstantImageFilter< KernelImageType, RealImageType > NormalizeFilterType;
typename NormalizeFilterType::Pointer normalizeFilter = NormalizeFilterType::New();
normalizeFilter->SetConstant( NumericTraits< RealPixelType >::OneValue() );
normalizeFilter->SetNumberOfThreads( this->GetNumberOfThreads() );
normalizeFilter->SetInput( this->GetKernelImage() );
normalizeFilter->ReleaseDataFlagOn();
progress->RegisterInternalFilter( normalizeFilter, 0.1f );
normalizeFilter->UpdateLargestPossibleRegion();
this->ComputeConvolution( normalizeFilter->GetOutput(), progress );
}
else
{
this->ComputeConvolution( this->GetKernelImage(), progress );
}
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage >
template< typename TImage >
void
ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >
::ComputeConvolution( const TImage * kernelImage,
ProgressAccumulator * progress )
{
typedef typename TImage::PixelType KernelImagePixelType;
typedef ImageKernelOperator< KernelImagePixelType, ImageDimension > KernelOperatorType;
KernelOperatorType kernelOperator;
bool kernelNeedsPadding = this->GetKernelNeedsPadding();
float optionalFilterWeights = 0.0f;
if ( this->GetNormalize() )
{
optionalFilterWeights += 0.1f;
}
if ( this->GetKernelNeedsPadding() )
{
optionalFilterWeights += 0.1f;
}
if ( this->GetOutputRegionMode() == Self::VALID )
{
optionalFilterWeights += 0.1f;
}
// Flip the kernel
typedef FlipImageFilter< TImage > FlipperType;
typename FlipperType::Pointer flipper = FlipperType::New();
typename FlipperType::FlipAxesArrayType axesArray;
axesArray.Fill( true );
flipper->SetFlipAxes( axesArray );
flipper->SetInput( kernelImage );
if ( kernelNeedsPadding )
{
// Pad the kernel if necessary to an odd size in each dimension.
typedef ConstantPadImageFilter< TImage, TImage > PadImageFilterType;
typename PadImageFilterType::Pointer kernelPadImageFilter = PadImageFilterType::New();
kernelPadImageFilter->SetConstant( NumericTraits< KernelImagePixelType >::ZeroValue() );
kernelPadImageFilter->SetPadLowerBound( this->GetKernelPadSize() );
kernelPadImageFilter->SetNumberOfThreads( this->GetNumberOfThreads() );
kernelPadImageFilter->ReleaseDataFlagOn();
kernelPadImageFilter->SetInput( flipper->GetOutput() );
progress->RegisterInternalFilter( kernelPadImageFilter, 0.1f );
kernelPadImageFilter->UpdateLargestPossibleRegion();
kernelOperator.SetImageKernel( kernelPadImageFilter->GetOutput() );
}
else
{
flipper->UpdateLargestPossibleRegion();
kernelOperator.SetImageKernel( flipper->GetOutput() );
}
KernelSizeType radius = this->GetKernelRadius( kernelImage );
kernelOperator.CreateToRadius( radius );
typename InputImageType::Pointer localInput = InputImageType::New();
localInput->Graft( this->GetInput() );
// The NeighborhoodOperatorImageFilter does all the work.
typedef NeighborhoodOperatorImageFilter< InputImageType, OutputImageType, KernelImagePixelType >
ConvolutionFilterType;
typename ConvolutionFilterType::Pointer convolutionFilter = ConvolutionFilterType::New();
convolutionFilter->SetOperator( kernelOperator );
convolutionFilter->OverrideBoundaryCondition( this->GetBoundaryCondition() );
convolutionFilter->SetInput( localInput );
convolutionFilter->SetNumberOfThreads( this->GetNumberOfThreads() );
convolutionFilter->ReleaseDataFlagOn();
progress->RegisterInternalFilter( convolutionFilter, 1.0f - optionalFilterWeights );
if ( this->GetOutputRegionMode() == Self::SAME )
{
// Graft the output of the convolution filter onto this filter's
// output.
convolutionFilter->GraftOutput( this->GetOutput() );
convolutionFilter->GetOutput()->SetRequestedRegion( this->GetOutput()->GetRequestedRegion() );
convolutionFilter->Update();
this->GraftOutput( convolutionFilter->GetOutput() );
}
else // OutputRegionMode == Self::VALID
{
typedef CropImageFilter< OutputImageType, OutputImageType > CropFilterType;
typedef typename CropFilterType::Pointer CropFilterPointer;
typedef typename CropFilterType::SizeType CropSizeType;
// Set up the crop sizes.
CropSizeType upperCropSize( radius );
CropSizeType lowerCropSize( radius );
convolutionFilter->GraftOutput( this->GetOutput() );
// For the lower crop, the crop size can be reduced by 1 in a
// dimension when the kernel size is odd in that dimension.
lowerCropSize -= this->GetKernelPadSize();
// Set up the crop filter.
CropFilterPointer cropFilter = CropFilterType::New();
cropFilter->SetLowerBoundaryCropSize( lowerCropSize );
cropFilter->SetUpperBoundaryCropSize( upperCropSize );
cropFilter->SetNumberOfThreads( this->GetNumberOfThreads() );
cropFilter->InPlaceOn();
progress->RegisterInternalFilter( cropFilter, 0.1f );
cropFilter->SetInput( convolutionFilter->GetOutput() );
// Graft the minipipeline output to this filter.
cropFilter->GetOutput()->SetRequestedRegion( this->GetOutput()->GetRequestedRegion() );
cropFilter->Update();
// Graft the output of the crop filter back onto this
// filter's output.
this->GraftOutput( cropFilter->GetOutput() );
}
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage >
bool
ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >
::GetKernelNeedsPadding() const
{
const KernelImageType *kernel = this->GetKernelImage();
InputRegionType kernelRegion = kernel->GetLargestPossibleRegion();
InputSizeType kernelSize = kernelRegion.GetSize();
for ( unsigned int i = 0; i < ImageDimension; i++ )
{
if ( kernelSize[i] % 2 == 0 ) // Check if dimension is even
{
return true;
}
}
return false;
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage >
typename ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >::KernelSizeType
ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >
::GetKernelPadSize() const
{
const KernelImageType *kernel = this->GetKernelImage();
KernelRegionType kernelRegion = kernel->GetLargestPossibleRegion();
KernelSizeType kernelSize = kernelRegion.GetSize();
KernelSizeType padSize;
for ( unsigned int i = 0; i < ImageDimension; i++)
{
// Pad by 1 if the size fo the image in this dimension is even.
padSize[i] = 1 - (kernelSize[i] % 2);
}
return padSize;
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage >
template< typename TImage >
typename ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >::KernelSizeType
ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >
::GetKernelRadius(const TImage *kernelImage) const
{
// Compute the kernel radius.
KernelSizeType radius;
for ( unsigned int i = 0; i < ImageDimension; i++ )
{
radius[i] = kernelImage->GetLargestPossibleRegion().GetSize()[i] / 2;
}
return radius;
}
template< typename TInputImage, typename TKernelImage, typename TOutputImage >
void
ConvolutionImageFilter< TInputImage, TKernelImage, TOutputImage >
::GenerateInputRequestedRegion()
{
// Pad the input image with the radius of the kernel.
if ( this->GetInput() )
{
InputRegionType inputRegion = this->GetOutput()->GetRequestedRegion();
// Pad the output request region by the kernel radius.
KernelSizeType radius = this->GetKernelRadius( this->GetKernelImage() );
inputRegion.PadByRadius( radius );
// Crop the output request region to fit within the largest
// possible region.
typename InputImageType::Pointer inputPtr =
const_cast< InputImageType * >( this->GetInput() );
bool cropped = inputRegion.Crop( inputPtr->GetLargestPossibleRegion() );
if ( !cropped )
{
InvalidRequestedRegionError e( __FILE__, __LINE__ );
e.SetLocation( ITK_LOCATION );
e.SetDescription( "Requested region is (at least partially) outside the largest possible region." );
e.SetDataObject( inputPtr );
throw e;
}
// Input is an image, cast away the constness so we can set
// the requested region.
inputPtr->SetRequestedRegion( inputRegion );
}
// Request the largest possible region for the kernel image.
if ( this->GetKernelImage() )
{
// Input kernel is an image, cast away the constness so we can set
// the requested region.
typename KernelImageType::Pointer kernelPtr =
const_cast< KernelImageType * >( this->GetKernelImage() );
kernelPtr->SetRequestedRegionToLargestPossibleRegion();
}
}
}
#endif
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