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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 itkBilateralImageFilter_h
#define itkBilateralImageFilter_h
#include "itkImageToImageFilter.h"
#include "itkFixedArray.h"
#include "itkNeighborhoodIterator.h"
#include "itkNeighborhood.h"
namespace itk
{
/**
* \class BilateralImageFilter
* \brief Blurs an image while preserving edges
*
* This filter uses bilateral filtering to blur an image using both
* domain and range "neighborhoods". Pixels that are close to a pixel
* in the image domain and similar to a pixel in the image range are
* used to calculate the filtered value. Two gaussian kernels (one in
* the image domain and one in the image range) are used to smooth
* the image. The result is an image that is smoothed in homogeneous
* regions yet has edges preserved. The result is similar to
* anisotropic diffusion but the implementation in non-iterative.
* Another benefit to bilateral filtering is that any distance metric
* can be used for kernel smoothing the image range. Hence, color
* images can be smoothed as vector images, using the CIE distances
* between intensity values as the similarity metric (the Gaussian
* kernel for the image domain is evaluated using CIE distances).
* A separate version of this filter will be designed for color
* and vector images.
*
* Bilateral filtering is capable of reducing the noise in an image
* by an order of magnitude while maintaining edges.
*
* The bilateral operator used here was described by Tomasi and
* Manduchi (Bilateral Filtering for Gray and ColorImages. IEEE
* ICCV. 1998.)
*
* \sa GaussianOperator
* \sa RecursiveGaussianImageFilter
* \sa DiscreteGaussianImageFilter
* \sa AnisotropicDiffusionImageFilter
* \sa Image
* \sa Neighborhood
* \sa NeighborhoodOperator
*
* \ingroup ImageEnhancement
* \ingroup ImageFeatureExtraction
* \todo Support color images
* \todo Support vector images
* \ingroup ITKImageFeature
*
* \wiki
* \wikiexample{Smoothing/BilateralImageFilter,Bilateral filter an image}
* \endwiki
*/
template< typename TInputImage, typename TOutputImage >
class ITK_TEMPLATE_EXPORT BilateralImageFilter:
public ImageToImageFilter< TInputImage, TOutputImage >
{
public:
/** Standard class typedefs. */
typedef BilateralImageFilter Self;
typedef ImageToImageFilter< TInputImage, TOutputImage > Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods). */
itkTypeMacro(BilateralImageFilter, ImageToImageFilter);
/** Image type information. */
typedef TInputImage InputImageType;
typedef TOutputImage OutputImageType;
/** Superclass typedefs. */
typedef typename Superclass::OutputImageRegionType OutputImageRegionType;
/** Extract some information from the image types. Dimensionality
* of the two images is assumed to be the same. */
typedef typename TOutputImage::PixelType OutputPixelType;
typedef typename TOutputImage::InternalPixelType OutputInternalPixelType;
typedef typename NumericTraits< OutputPixelType >::RealType OutputPixelRealType;
typedef typename TInputImage::PixelType InputPixelType;
typedef typename TInputImage::InternalPixelType InputInternalPixelType;
/** Extract some information from the image types. Dimensionality
* of the two images is assumed to be the same. */
itkStaticConstMacro(ImageDimension, unsigned int,
TOutputImage::ImageDimension);
/** Typedef of double containers */
typedef FixedArray< double, itkGetStaticConstMacro(ImageDimension) > ArrayType;
/** Neighborhood iterator types. */
typedef ConstNeighborhoodIterator< TInputImage > NeighborhoodIteratorType;
/** Kernel typedef. */
typedef
Neighborhood< double, itkGetStaticConstMacro(ImageDimension) > KernelType;
typedef typename KernelType::SizeType SizeType;
typedef typename KernelType::SizeValueType SizeValueType;
/** Kernel iterator. */
typedef typename KernelType::Iterator KernelIteratorType;
typedef typename KernelType::ConstIterator KernelConstIteratorType;
/** Gaussian image type */
typedef
Image< double, itkGetStaticConstMacro(ImageDimension) > GaussianImageType;
/** Standard get/set macros for filter parameters.
* DomainSigma is specified in the same units as the Image spacing.
* RangeSigma is specified in the units of intensity. */
itkSetMacro(DomainSigma, ArrayType);
itkGetConstMacro(DomainSigma, const ArrayType);
itkSetMacro(DomainMu, double);
itkGetConstReferenceMacro(DomainMu, double);
itkSetMacro(RangeSigma, double);
itkGetConstMacro(RangeSigma, double);
itkGetConstMacro(FilterDimensionality, unsigned int);
itkSetMacro(FilterDimensionality, unsigned int);
/** Convenience get/set methods for setting all domain parameters to the
* same values. */
void SetDomainSigma(const double v)
{
m_DomainSigma.Fill(v);
}
/** Control automatic kernel size determination. When
* automatic is "on", the kernel size is a function of the domain
* sigma. When automatic is "off", the kernel size is whatever is
* specified by the user.
* \sa SetRadius() */
itkBooleanMacro(AutomaticKernelSize);
itkGetConstMacro(AutomaticKernelSize, bool);
itkSetMacro(AutomaticKernelSize, bool);
/** Set/Get the kernel radius, specified in pixels. This parameter
* is used only when AutomaticNeighborhoodSize is "off". */
void SetRadius(const SizeValueType);
itkSetMacro(Radius, SizeType);
itkGetConstReferenceMacro(Radius, SizeType);
/** Set/Get the number of samples in the approximation to the Gaussian
* used for the range smoothing. Samples are only generated in the
* range of [0, 4*m_RangeSigma]. Default is 100. */
itkSetMacro(NumberOfRangeGaussianSamples, unsigned long);
itkGetConstMacro(NumberOfRangeGaussianSamples, unsigned long);
#ifdef ITK_USE_CONCEPT_CHECKING
// Begin concept checking
itkConceptMacro( OutputHasNumericTraitsCheck,
( Concept::HasNumericTraits< OutputPixelType > ) );
// End concept checking
#endif
protected:
/** Constructor. */
BilateralImageFilter();
/** Destructor. */
virtual ~BilateralImageFilter() ITK_OVERRIDE {}
/** PrintSelf. */
void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
/** Do some setup before the ThreadedGenerateData */
void BeforeThreadedGenerateData() ITK_OVERRIDE;
/** Standard pipeline method. This filter is implemented as a multi-threaded
* filter. */
void ThreadedGenerateData(const OutputImageRegionType & outputRegionForThread,
ThreadIdType threadId) ITK_OVERRIDE;
/** BilateralImageFilter needs a larger input requested region than
* the output requested region (larger by the size of the domain
* Gaussian kernel). As such, BilateralImageFilter needs to provide
* an implementation for GenerateInputRequestedRegion() in order to
* inform the pipeline execution model.
* \sa ImageToImageFilter::GenerateInputRequestedRegion() */
virtual void GenerateInputRequestedRegion() ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(BilateralImageFilter);
/** The standard deviation of the gaussian blurring kernel in the image
range. Units are intensity. */
double m_RangeSigma;
/** The standard deviation of the gaussian blurring kernel in each
dimensional direction. Units match image spacing units. */
ArrayType m_DomainSigma;
/** Multiplier used to define statistical thresholds. Gaussians are
* only evaluated to m_DomainMu*m_DomainSigma or m_RangeMu*m_RangeSigma. */
double m_DomainMu;
double m_RangeMu;
/** Number of dimensions to process. Default is all dimensions */
unsigned int m_FilterDimensionality;
/** Gaussian kernel used for smoothing in the spatial domain */
KernelType m_GaussianKernel;
SizeType m_Radius;
bool m_AutomaticKernelSize;
/** Variables for the lookup table of range gaussian values */
unsigned long m_NumberOfRangeGaussianSamples;
double m_DynamicRange;
double m_DynamicRangeUsed;
std::vector< double > m_RangeGaussianTable;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkBilateralImageFilter.hxx"
#endif
#endif
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