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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 itkHistogramToRunLengthFeaturesFilter_h
#define itkHistogramToRunLengthFeaturesFilter_h
#include "itkHistogram.h"
#include "itkMacro.h"
#include "itkProcessObject.h"
#include "itkSimpleDataObjectDecorator.h"
namespace itk {
namespace Statistics {
/** \class HistogramToRunLengthFeaturesFilter
* \brief This class computes texture feature coefficients from a grey level
* run-length matrix.
*
* By default, run length features are computed for each spatial
* direction and then averaged afterward, so it is possible to access the
* standard deviations of the texture features. These values give a clue as
* to texture anisotropy. However, doing this is much more work, because it
* involved computing one for each offset given. To compute a single matrix
* using the first offset, call FastCalculationsOn(). If this is called,
* then the texture standard deviations will not be computed (and will be set
* to zero), but texture computation will be much faster.
*
* This class is templated over the input histogram type.
*
* Print 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.
*
* IJ article: https://hdl.handle.net/1926/1374
*
* \sa ScalarImageToRunLengthFeaturesFilter
* \sa ScalarImageToRunLengthMatrixFilter
* \sa HistogramToRunLengthFeaturesFilter
*
* \author: Nick Tustison
* \ingroup ITKStatistics
*/
template< typename THistogram >
class ITK_TEMPLATE_EXPORT HistogramToRunLengthFeaturesFilter : public ProcessObject
{
public:
/** Standard typedefs */
typedef HistogramToRunLengthFeaturesFilter Self;
typedef ProcessObject Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Run-time type information (and related methods). */
itkTypeMacro( HistogramToRunLengthFeaturesFilter, ProcessObject );
/** standard New() method support */
itkNewMacro( Self );
typedef THistogram HistogramType;
typedef typename HistogramType::Pointer HistogramPointer;
typedef typename HistogramType::ConstPointer HistogramConstPointer;
typedef typename HistogramType::MeasurementType MeasurementType;
typedef typename HistogramType::MeasurementVectorType MeasurementVectorType;
typedef typename HistogramType::IndexType IndexType;
typedef typename HistogramType::
TotalAbsoluteFrequencyType FrequencyType;
/** Method to Set/Get the input Histogram */
using Superclass::SetInput;
void SetInput ( const HistogramType * histogram );
const HistogramType * GetInput() const;
/** Smart Pointer type to a DataObject. */
typedef DataObject::Pointer DataObjectPointer;
/** Type of DataObjects used for scalar outputs */
typedef SimpleDataObjectDecorator<MeasurementType> MeasurementObjectType;
/** Methods to return the short run emphasis. */
MeasurementType GetShortRunEmphasis() const;
const MeasurementObjectType* GetShortRunEmphasisOutput() const;
/** Methods to return the long run emphasis. */
MeasurementType GetLongRunEmphasis() const;
const MeasurementObjectType* GetLongRunEmphasisOutput() const;
/** Methods to return the grey level nonuniformity. */
MeasurementType GetGreyLevelNonuniformity() const;
const MeasurementObjectType* GetGreyLevelNonuniformityOutput() const;
/** Methods to return the run length nonuniformity. */
MeasurementType GetRunLengthNonuniformity() const;
const MeasurementObjectType* GetRunLengthNonuniformityOutput() const;
/** Methods to return the low grey level run emphasis. */
MeasurementType GetLowGreyLevelRunEmphasis() const;
const MeasurementObjectType* GetLowGreyLevelRunEmphasisOutput() const;
/** Methods to return the high grey level run emphasis. */
MeasurementType GetHighGreyLevelRunEmphasis() const;
const MeasurementObjectType* GetHighGreyLevelRunEmphasisOutput() const;
/** Methods to return the short run low grey level run emphasis. */
MeasurementType GetShortRunLowGreyLevelEmphasis() const;
const MeasurementObjectType* GetShortRunLowGreyLevelEmphasisOutput() const;
/** Methods to return the short run high grey level run emphasis. */
MeasurementType GetShortRunHighGreyLevelEmphasis() const;
const MeasurementObjectType* GetShortRunHighGreyLevelEmphasisOutput() const;
/** Methods to return the long run low grey level run emphasis. */
MeasurementType GetLongRunLowGreyLevelEmphasis() const;
const MeasurementObjectType* GetLongRunLowGreyLevelEmphasisOutput() const;
/** Methods to return the long run high grey level run emphasis. */
MeasurementType GetLongRunHighGreyLevelEmphasis() const;
const MeasurementObjectType* GetLongRunHighGreyLevelEmphasisOutput() const;
itkGetMacro( TotalNumberOfRuns, unsigned long );
/** Run-length feature types */
typedef enum
{
ShortRunEmphasis,
LongRunEmphasis,
GreyLevelNonuniformity,
RunLengthNonuniformity,
LowGreyLevelRunEmphasis,
HighGreyLevelRunEmphasis,
ShortRunLowGreyLevelEmphasis,
ShortRunHighGreyLevelEmphasis,
LongRunLowGreyLevelEmphasis,
LongRunHighGreyLevelEmphasis
} RunLengthFeatureName;
/** convenience method to access the run length values */
MeasurementType GetFeature( RunLengthFeatureName name );
protected:
HistogramToRunLengthFeaturesFilter();
~HistogramToRunLengthFeaturesFilter() ITK_OVERRIDE {};
virtual void PrintSelf(std::ostream& os, Indent indent) const ITK_OVERRIDE;
/** Make a DataObject to be used for output output. */
typedef ProcessObject::DataObjectPointerArraySizeType DataObjectPointerArraySizeType;
using Superclass::MakeOutput;
virtual DataObjectPointer MakeOutput( DataObjectPointerArraySizeType ) ITK_OVERRIDE;
virtual void GenerateData() ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(HistogramToRunLengthFeaturesFilter);
unsigned long m_TotalNumberOfRuns;
};
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkHistogramToRunLengthFeaturesFilter.hxx"
#endif
#endif
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