#include <itkScalarImageToRunLengthMatrixFilter.h>

Inheritance diagram for itk::Statistics::ScalarImageToRunLengthMatrixFilter< TImageType, THistogramFrequencyContainer >:

Collaboration diagram for itk::Statistics::ScalarImageToRunLengthMatrixFilter< TImageType, THistogramFrequencyContainer >:

List of all members.

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef HistogramType::ConstPointer	HistogramConstPointer
typedef HistogramType::Pointer	HistogramPointer
typedef Histogram < MeasurementType, THistogramFrequencyContainer >	HistogramType
typedef ImageType::ConstPointer	ImageConstPointer
typedef ImageType::Pointer	ImagePointer
typedef TImageType	ImageType
typedef ImageType::IndexType	IndexType
typedef NumericTraits < PixelType >::RealType	MeasurementType
typedef HistogramType::MeasurementVectorType	MeasurementVectorType
typedef ImageType::OffsetType	OffsetType
typedef VectorContainer < unsigned char, OffsetType >	OffsetVector
typedef OffsetVector::Pointer	OffsetVectorPointer
typedef ImageType::PixelType	PixelType
typedef SmartPointer< Self >	Pointer
typedef ImageType::PointType	PointType
typedef ImageType::SizeType	RadiusType
typedef NumericTraits < PixelType >::RealType	RealType
typedef ImageType::RegionType	RegionType
typedef ScalarImageToRunLengthMatrixFilter	Self
typedef ProcessObject	Superclass
Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
const ImageType *	GetInput () const
const ImageType *	GetMaskImage () const
virtual PixelType	GetMax () const
virtual RealType	GetMaxDistance () const
virtual PixelType	GetMin () const
virtual RealType	GetMinDistance () const
virtual const char *	GetNameOfClass () const
virtual unsigned int	GetNumberOfBinsPerAxis () const
virtual const OffsetVector *	GetOffsets ()
const HistogramType *	GetOutput () const
void	SetDistanceValueMinMax (RealType min, RealType max)
void	SetInput (const ImageType *image)
void	SetMaskImage (const ImageType *image)
virtual void	SetNumberOfBinsPerAxis (unsigned int _arg)
void	SetOffset (const OffsetType offset)
virtual void	SetOffsets (OffsetVector *_arg)
void	SetPixelValueMinMax (PixelType min, PixelType max)

virtual void	SetInsidePixelValue (PixelType _arg)
virtual PixelType	GetInsidePixelValue () const
Static Public Member Functions
static Pointer	New ()
Static Public Attributes
static const unsigned int	DefaultBinsPerAxis = 256
static const unsigned int	ImageDimension = TImageType::ImageDimension
Protected Types
typedef DataObject::Pointer	DataObjectPointer
typedef ProcessObject::DataObjectPointerArraySizeType	DataObjectPointerArraySizeType
Protected Member Functions
virtual void	GenerateData ()
virtual DataObjectPointer	MakeOutput (DataObjectPointerArraySizeType idx)
void	NormalizeOffsetDirection (OffsetType &offset)
void	PrintSelf (std::ostream &os, Indent indent) const
	ScalarImageToRunLengthMatrixFilter ()
virtual	~ScalarImageToRunLengthMatrixFilter ()
Private Attributes
PixelType	m_InsidePixelValue
MeasurementVectorType	m_LowerBound
PixelType	m_Max
RealType	m_MaxDistance
PixelType	m_Min
RealType	m_MinDistance
unsigned int	m_NumberOfBinsPerAxis
OffsetVectorPointer	m_Offsets
MeasurementVectorType	m_UpperBound

Detailed Description

template<class TImageType, class THistogramFrequencyContainer = DenseFrequencyContainer2>
class itk::Statistics::ScalarImageToRunLengthMatrixFilter< TImageType, THistogramFrequencyContainer >

This class computes a run length matrix (histogram) from a given image and a mask image if provided. Run length matrces are used for image texture description.

This filters creates a grey-level run length matrix from a N-D scalar image. This is another possible texture description. See the following references. M. M. Galloway. Texture analysis using gray level run lengths. Computer Graphics and Image Processing, 4:172-179, 1975.

A. Chu, C. M. Sehgal, and J. F. Greenleaf. Use of gray value distribution of run lengths for texture analysis. Pattern Recognition Letters, 11:415-420, 1990.

B. R. Dasarathy and E. B. Holder. Image characterizations based on joint gray-level run-length distributions. Pattern Recognition Letters, 12:490-502, 1991.

The basic idea is as follows: Given an image and an offset (e.g. (1, -1) for a 2-d image), each element in the joint histogram describes the frequency for a particular distance/ intensity pair within a given image. This distance/intensity pair can be described as follows: we start at a given voxel which has some intensity. We then "jump" to neighboring pixels in increments provided by the offset(s) as long as the pixel to which we are jumping is within the same intensity bin as the original voxel. The distance component is given by the distance from the original to the final voxel satisfying our jumping criteria.

The offset (or offsets) along which the co-occurences are calculated can be set by the user. Traditionally, only one offset is used per histogram, and offset components in the range [-1, 1] are used. For rotation-invariant features averages of features computed over several histograms with different offsets are generally used, instead of computing features from one histogram create with several offsets. Additionally, instead of using offsets of two or more pixels in any direction, multi-resolution techniques (e.g. image pyramids) are generally used to deal with texture at different spatial resolutions.

This class calculates a 2-d histogram of all the intensity/distance pairs in the given image's requested region, for a given set of offsets. That is, if a given offset falls outside of the requested region (or outside the mask) at a particular point, that distance/intensity pair will not be added to the matrix.

The number of histogram bins on each axis can be set (defaults to 256). Also, by default the histogram min and max corresponds to the largest and smallest possible pixel value of that pixel type. To customize the histogram bounds for a given image, the max and min pixel values that will be placed in the histogram can be set manually. NB: The min and max are INCLUSIVE.

Further, the type of histogram frequency container used is an optional template parameter. By default, a dense container is used, but for images with little texture or in cases where the user wants more histogram bins, a sparse container can be used for the histogram instead.

WARNING: This probably won't work for pixels of double or long-double type unless you set the histogram min and max manually. This is because the largest histogram bin by default has max value of the largest possible pixel value plus 1. For double and long-double types, whose "RealType" as defined by the NumericTraits class is the same, and thus cannot hold any larger values, this would cause a float overflow.

IJ article: http://hdl.handle.net/1926/1374

See also:: ScalarImageToRunLengthFeaturesFilter; ScalarImageToRunLengthMatrixFilter; HistogramToRunLengthFeaturesFilter

Author:: : Nick Tustison

Definition at line 106 of file itkScalarImageToRunLengthMatrixFilter.h.