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Class Hierarchy
This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 1234]
 CAbsPowerSum< N >Basic statistic. AbsPowerSum<N> = $ \sum_i |x_i|^N $
 CAccumulatorChain< T, Selected, dynamic >Create an accumulator chain containing the selected statistics and their dependencies
 CAccumulatorChain< T, Selected, true >
 CAccumulatorChainArray< T, Selected, dynamic >Create an array of accumulator chains containing the selected per-region and global statistics and their dependencies
 CAccumulatorChainArray< T, Selected, true >
 CArgMaxWeightBasic statistic. Data where weight assumes its maximal value
 CArgMinWeightBasic statistic. Data value where weight assumes its minimal value
 CArrayOfRegionStatistics< RegionStatistics, LabelType >Calculate statistics for all regions of a labeled image
 CArrayVectorView< T >
 CArrayVectorView< ARITHTYPE >
 CArrayVectorView< AxisInfo >
 CArrayVectorView< BinType >
 CArrayVectorView< bool >
 CArrayVectorView< ClassLabelType >
 CArrayVectorView< DecisionTree_t >
 CArrayVectorView< detail::DecisionTreeDeprec >
 CArrayVectorView< double >
 CArrayVectorView< hsize_t >
 CArrayVectorView< ImageType >
 CArrayVectorView< IndexType >
 CArrayVectorView< INT >
 CArrayVectorView< int >
 CArrayVectorView< Int32 >
 CArrayVectorView< Label_t >
 CArrayVectorView< Matrix< Complex > >
 CArrayVectorView< MultiArrayIndex >
 CArrayVectorView< npy_intp >
 CArrayVectorView< RegionAccumulatorChain >
 CArrayVectorView< Segment >
 CArrayVectorView< size_t >
 CArrayVectorView< std::pair< Int32, double > >
 CArrayVectorView< std::ptrdiff_t >
 CArrayVectorView< std::queue< ValueType > >
 CArrayVectorView< unsigned char >
 CAutoRangeHistogram< BinCount >Histogram where range mapping bounds are defined by minimum and maximum of data
 CBasicImage< PIXELTYPE, Alloc >Fundamental class template for images
 CBasicImage< double >
 CBasicImage< InternalValue >
 CBasicImage< TinyVector< double, 2 > >
 CBasicImage< value_type >
 CBasicImage< VALUETYPE >
 CBasicImageIteratorBase< IMAGEITERATOR, PIXELTYPE, REFERENCE, POINTER, LINESTARTITERATOR >
 CBasicImageIteratorBase< BasicImageIterator< PIXELTYPE, ITERATOR >, PIXELTYPE, PIXELTYPE &, PIXELTYPE *, ITERATOR >
 CBasicImageIteratorBase< ConstBasicImageIterator< PIXELTYPE, ITERATOR >, PIXELTYPE, PIXELTYPE const &, PIXELTYPE const *, ITERATOR >
 CBasicImageView< PIXELTYPE >BasicImage using foreign memory
 CBestGiniOfColumn< LineSearchLossTag >
 CBestGiniOfColumn< vigra::GiniCriterion >
 CBilinearInterpolatingAccessor< ACCESSOR, VALUETYPE >Bilinear interpolation at non-integer positions
 CBlueAccessor< RGBVALUE >
 CBox< VALUETYPE, DIMENSION >Represent an n-dimensional box as a (begin, end) pair. Depending on the value type, end() is considered to be outside the box (as in the STL, for integer types), or inside (for floating point types). size() will always be end() - begin()
 CBrightnessContrastFunctor< PixelType >Adjust brightness and contrast of an image
 CBrightnessContrastFunctor< ComponentType >
 CBrightnessContrastFunctor< unsigned char >
 CBSplineBase< ORDER, T >
 CBSplineBase< ORDER, double >
 CBucketQueue< ValueType, Ascending >Priority queue implemented using bucket sort
 CCatmullRomSpline< T >
 CCentral< A >Modifier. Substract mean before computing statistic
 CCentral< PowerSum< 2 > >Spezialization: works in pass 1, operator+=() supported (merging supported)
 CCentral< PowerSum< 3 > >Specialization: works in pass 2, operator+=() supported (merging supported)
 CCentral< PowerSum< 4 > >Specialization: works in pass 2, operator+=() supported (merging supported)
 CCentralMoment< N >Alias. CentralMoment<N>
 Ccl_charNAccessor_COMP
 Ccl_TYPE3WriteAccessor_s1
 Ccl_TYPE3WriteAccessor_s2
 CColumnIterator< IMAGE_ITERATOR >Iterator adapter to linearly access columns
 CConstValueIterator< PIXELTYPE >Iterator that always returns the constant specified in the constructor
 CConvolutionOptions< dim >Options class template for convolutions
 CCoord< A >Modifier. Compute statistic from pixel coordinates rather than from pixel values
 CCoordinateConstValueAccessor< Accessor, COORD >Forward accessor to the value() part of the values an iterator points to
 CCoordinateSystemBasic statistic. Identity matrix of appropriate size
 CCorrectStatus
 CCoscotFunction< T >
 CCoupledHandle< T, NEXT >
 CCoupledIteratorType< N, T1, T2, T3, T4, T5 >
 CCoupledScanOrderIterator< N, HANDLES, DIMENSION >Iterate over multiple images simultaneously in scan order
 CCrackContourCirculator< IMAGEITERATOR >Circulator that walks around a given region
 CDataArg< INDEX >Specifies index of data in CoupledHandle
 CDiff2DTwo dimensional difference vector
 CDiffusivityFunctor< Value >Diffusivity functor for non-linear diffusion
 CDist2D
 CDivideByCount< A >Modifier. Divide statistic by Count: DivideByCount<TAG> = TAG / Count
 CDivideUnbiased< A >Modifier. Divide statistics by Count-1: DivideUnbiased<TAG> = TAG / (Count-1)
 CDraw< T1, T2, C1, C2 >
 CDT_StackEntry< Iter >
 CEarlyStoppStdStandard early stopping criterion
 CEdgel
 CEntropyCriterion
 CFFTWComplex< Real >Wrapper class for the FFTW complex types 'fftw_complex'
 CFFTWConvolvePlan< N, Real >
 CFFTWImaginaryAccessor< Real >
 CFFTWMagnitudeAccessor< Real >
 CFFTWPhaseAccessor< Real >
 CFFTWPlan< N, Real >
 CFFTWRealAccessor< Real >
 CFFTWSquaredMagnitudeAccessor< Real >
 CFindAverage< VALUETYPE >Find the average pixel value in an image or ROI
 CFindAverageAndVariance< VALUETYPE >Find the average pixel value and its variance in an image or ROI
 CFindBoundingRectangleCalculate the bounding rectangle of an ROI in an image
 CFindMinMax< VALUETYPE >Find the minimum and maximum pixel value in an image or ROI
 CFindROISize< VALUETYPE >Calculate the size of an ROI in an image
 CFindSum< VALUETYPE >Find the sum of the pixel values in an image or ROI
 CFixedPoint< IntBits, FractionalBits >
 CFixedPoint16< IntBits, OverflowHandling >
 CFlatScatterMatrixBasic statistic. Flattened uppter-triangular part of scatter matrix
 CFunctorTraits< T >Export associated information for a functor
 CGammaFunctor< PixelType >Perform gamma correction of an image
 CGammaFunctor< ComponentType >
 CGammaFunctor< unsigned char >
 CGaussian< T >
 CGetClusterVariables
 CGiniCriterion
 CGlobal< A >Modifier. Compute statistic globally rather than per region
 CGlobalRangeHistogram< BinCount >Like AutoRangeHistogram, but use global min/max rather than region min/max
 CGrayToRGBAccessor< VALUETYPE >
 CGreenAccessor< RGBVALUE >
 CHC_Entry
 CHClustering
 CHDF5FileAccess to HDF5 files
 CHDF5HandleWrapper for hid_t objects
 CHDF5ImportInfoArgument object for the function readHDF5()
 CHistogramOptionsSet histogram options
 CImageArray< ImageType, Alloc >Fundamental class template for arrays of equal-sized images
 CImageExportInfoArgument object for the function exportImage()
 CImageImportInfoArgument object for the function importImage()
 CImageIteratorBase< IMAGEITERATOR, PIXELTYPE, REFERENCE, POINTER, StridedOrUnstrided >Base class for 2D random access iterators
 CImageIteratorBase< ConstImageIterator< PIXELTYPE >, PIXELTYPE, PIXELTYPE const &, PIXELTYPE const * >
 CImageIteratorBase< ConstStridedImageIterator< PIXELTYPE >, PIXELTYPE, PIXELTYPE const &, PIXELTYPE const *, StridedArrayTag >
 CImageIteratorBase< ImageIterator< PIXELTYPE >, PIXELTYPE, PIXELTYPE &, PIXELTYPE * >
 CImageIteratorBase< StridedImageIterator< PIXELTYPE >, PIXELTYPE, PIXELTYPE &, PIXELTYPE *, StridedArrayTag >
 CImagePyramid< ImageType, Alloc >Class template for logarithmically tapering image pyramids
 CIntegerHistogram< BinCount >Histogram where data values are equal to bin indices
 CIteratorAdaptor< Policy >Quickly create 1-dimensional iterator adapters
 CIteratorTraits< T >Export associated information for each image iterator
 CKernel1D< ARITHTYPE >Generic 1 dimensional convolution kernel
 CKernel2D< ARITHTYPE >Generic 2 dimensional convolution kernel
 CKurtosisBasic statistic. Kurtosis
 CLab2RGBFunctor< T >Convert perceptual uniform CIE L*a*b* into linear (raw) RGB
 CLab2RGBPrimeFunctor< T >Convert perceptual uniform CIE L*a*b* into non-linear (gamma corrected) R'G'B'
 CLab2XYZFunctor< T >Convert perceptual uniform CIE L*a*b* into standardized tri-stimulus XYZ
 CLab2XYZFunctor< component_type >
 CLabelArg< INDEX >Specifies index of labels in CoupledHandle
 CLastValueFunctor< VALUETYPE >Stores and returns the last value it has seen
 CLeastAngleRegressionOptionsPass options to leastAngleRegression()
 CLineIterator< IMAGE_ITERATOR >Iterator adapter to iterate along an arbitrary line on the image
 CLocalMinmaxOptionsOptions object for localMinima() and localMaxima()
 CLuv2RGBFunctor< T >Convert perceptual uniform CIE L*u*v* into linear (raw) RGB
 CLuv2RGBPrimeFunctor< T >Convert perceptual uniform CIE L*u*v* into non-linear (gamma corrected) R'G'B'
 CLuv2XYZFunctor< T >Convert perceptual uniform CIE L*u*v* into standardized tri-stimulus XYZ
 CLuv2XYZFunctor< component_type >
 CMagnitudeFunctor< ValueType >
 CMaximumBasic statistic. Maximum value
 CMedian
 CMeshGridAccessor
 CMinimumBasic statistic. Minimum value
 CMoment< N >Alias. Moment<N>
 CMultiArrayNavigator< MULTI_ITERATOR, N >A navigator that provides access to the 1D subranges of an n-dimensional range given by a vigra::MultiIterator and an nD shape
 CMultiArrayShape< N >
 CMultiArrayShape< actual_dimension >
 CMultiArrayShape< dim >
 CMultiArrayShape< Dimensions >
 CMultiArrayView< N, T, C >Base class for, and view to, vigra::MultiArray
 CMultiArrayView< 1, T, StridedArrayTag >
 CMultiArrayView< 2, double >
 CMultiArrayView< 2, int >
 CMultiArrayView< 2, LabelInt >
 CMultiArrayView< 2, T, C1 >
 CMultiArrayView< 2, T, C2 >
 CMultiArrayView< 2, T1, C1 >
 CMultiArrayView< 2, T2, C2 >
 CMultiArrayView< 2, UInt8 >
 CMultiArrayView< 2, VALUETYPE, StridedOrUnstrided >
 CMultiArrayView< N, Complex >
 CMultiArrayView< N, double >
 CMultiArrayView< N, int >
 CMultiArrayView< N, LabelInt >
 CMultiArrayView< N, NumpyArrayTraits< N, T, Stride >::value_type, Stride >
 CMultiArrayView< N, Real, UnstridedArrayTag >
 CMultiArrayView< N, T >
 CMultiArrayView< N, T, StrideTag >
 CMultiArrayView< N, T, UnstridedArrayTag >
 CMultiCoordinateNavigator< Dimensions, N >A navigator that provides access to the 1D subranges of an n-dimensional range given by an nD shape
 CMultiImageAccessor2< Iter1, Acc1, Iter2, Acc2 >Access two images simultaneously
 CMultiIterator< N, T, REFERENCE, POINTER >A multi-dimensional hierarchical iterator to be used with vigra::MultiArrayView if it is not strided
 CNeighborCodeEncapsulation of direction management for 4-neighborhood
 CNeighborCodeEncapsulation of direction management for the 8-neighborhood
 CNeighborCode3DEncapsulation of direction management of neighbors for a 3D 6-neighborhood
 CNeighborCode3DEncapsulation of direction management of neighbors for a 3D 26-neighborhood
 CNeighborhoodCirculator< IMAGEITERATOR, NEIGHBORCODE >Circulator that walks around a given location in a given image
 CNeighborhoodCirculator< IMAGEITERATOR, EightNeighborCode >
 CNeighborOffsetCirculator< NEIGHBORCODE >Circulator that walks around a given location
 CNodeBase
 CNoiseNormalizationOptionsPass options to one of the noise normalization functions
 CNormalizeStatus
 CNormalRandomFunctor< Engine >
 CNumpyAnyArray
 CPermuteCluster< Iter, DT >
 CPLSAOptionsOption object for the pLSA algorithm
 CPolynomialView< T >
 CPowerSum< N >Basic statistic. PowerSum<N> = $ \sum_i x_i^N $
 CPrincipal< A >Modifier. Project onto PCA eigenvectors
 CPrincipal< CoordinateSystem >Specialization (covariance eigenvectors): works in pass 1, operator+=() supported (merging)
 CPrincipal< PowerSum< 2 > >Specialization (covariance eigenvalues): works in pass 1, operator+=() supported (merging)
 CPriorityQueue< ValueType, PriorityType, Ascending >Heap-based priority queue compatible to BucketQueue
 CProblemSpec< LabelType >Problem specification class for the random forest
 CProcessor< Tag, LabelType, T1, C1, T2, C2 >
 CProcessor< ClassificationTag, LabelType, T1, C1, T2, C2 >
 CProcessor< RegressionTag, LabelType, T1, C1, T2, C2 >
 CQuaternion< ValueType >
 CRandomForest< LabelType, PreprocessorTag >
 CRandomForestClassCounter< DataSource, CountArray >
 CRandomForestOptionsOptions object for the random forest
 CRandomNumberGenerator< Engine >
 CRandomSplitOfColumn
 CRational< IntType >
 CRect2DTwo dimensional rectangle
 CRedAccessor< RGBVALUE >
 CReduceFunctor< FUNCTOR, VALUETYPE >Apply a functor to reduce the dimensionality of an array
 CRFErrorCallback
 CRGB2LabFunctor< T >Convert linear (raw) RGB into perceptual uniform CIE L*a*b*
 CRGB2LuvFunctor< T >Convert linear (raw) RGB into perceptual uniform CIE L*u*v*
 CRGB2RGBPrimeFunctor< From, To >Convert linear (raw) RGB into non-linear (gamma corrected) R'G'B'
 CRGB2sRGBFunctor< From, To >Convert linear (raw) RGB into standardized sRGB
 CRGB2XYZFunctor< T >Convert linear (raw) RGB into standardized tri-stimulus XYZ
 CRGBGradientMagnitudeFunctor< ValueType >
 CRGBPrime2LabFunctor< T >Convert non-linear (gamma corrected) R'G'B' into perceptual uniform CIE L*a*b*
 CRGBPrime2LuvFunctor< T >Convert non-linear (gamma corrected) R'G'B' into perceptual uniform CIE L*u*v*
 CRGBPrime2RGBFunctor< From, To >Convert non-linear (gamma corrected) R'G'B' into non-linear (raw) RGB
 CRGBPrime2XYZFunctor< T >Convert non-linear (gamma corrected) R'G'B' into standardized tri-stimulus XYZ
 CRGBPrime2YPrimeCbCrFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'CbCr color difference components
 CRGBPrime2YPrimeIQFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'IQ components
 CRGBPrime2YPrimePbPrFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'PbPr color difference components
 CRGBPrime2YPrimeUVFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'UV components
 CRGBToGrayAccessor< RGBVALUE >
 CRootDivideByCount< A >Modifier. RootDivideByCount<TAG> = sqrt( TAG/Count )
 CRootDivideUnbiased< A >Modifier. RootDivideUnbiased<TAG> = sqrt( TAG / (Count-1) )
 CRowIterator< IMAGE_ITERATOR >Iterator adapter to linearly access row
 CSampler< Random >Create random samples from a sequence of indices
 CSamplerOptionsOptions object for the Sampler class
 CScatterMatrixEigensystem
 CSeedOptionsOptions object for generateWatershedSeeds()
 CSeedRgDirectValueFunctor< Value >Statistics functor to be used for seeded region growing
 CSelect< T01, T02, T03, T04, T05, T06, T07, T08, T09, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19, T20 >Wrapper for MakeTypeList that additionally performs tag standardization
 CSIFImportInfoExtracts image properties from an Andor SIF file header
 CSkewnessBasic statistic. Skewness
 CSlantedEdgeMTFOptionsPass options to one of the slantedEdgeMTF() functions
 CSortSamplesByDimensions< DataMatrix >
 CSplice< T >
 CSplineImageView< ORDER, VALUETYPE >Create a continuous view onto a discrete image using splines
 CSplineImageView0< VALUETYPE, INTERNAL_TRAVERSER >Create an image view for nearest-neighbor interpolation
 CSplineImageView0< VALUETYPE >
 CSplineImageView1< VALUETYPE, INTERNAL_TRAVERSER >Create an image view for bi-linear interpolation
 CSplineImageView1< VALUETYPE >
 CSplitBase< Tag >
 CsRGB2RGBFunctor< From, To >Convert standardized sRGB into non-linear (raw) RGB
 CStandardAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
 CStandardAccessor< RGBVALUE >
 CStandardAccessor< SEQUENCE >
 CStandardAccessor< VECTOR >
 CStandardConstAccessor< VALUETYPE >Encapsulate read access to the values an iterator points to
 CStandardConstValueAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
 CStandardQuantiles< Hist >Compute (0%, 10%, 25%, 50%, 75%, 90%, 100%) quantiles from given histogram
 CStandardValueAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
 CStopBase
 CStridedArrayTag
 CStridedMultiIterator< N, T, REFERENCE, POINTER >A multi-dimensional hierarchical iterator to be used with vigra::MultiArrayView if it is not strided
 CStridedScanOrderIterator< N, T, REFERENCE, POINTER, M >Sequential iterator for MultiArrayView
 CThreshold< SrcValueType, DestValueType >Threshold an image
 CTinyVectorBase< V1, SIZE, D1, D2 >Base class for fixed size vectors
 CTinyVectorBase< double, SIZE, double[SIZE], TinyVector< double, SIZE > >
 CTinyVectorBase< float, SIZE, float[SIZE], TinyVector< float, SIZE > >
 CTinyVectorBase< T, SIZE, T *, TinyVectorView< T, SIZE > >
 CTinyVectorBase< T, SIZE, T[SIZE], TinyVector< T, SIZE > >
 CTinyVectorBase< ValueType, SIZE, ValueType[SIZE], TinyVector< ValueType, SIZE > >
 CTinyVectorBase< VALUETYPE, SIZE, VALUETYPE[SIZE], TinyVector< VALUETYPE, SIZE > >
 CUnbiasedKurtosisBasic statistic. Unbiased Kurtosis
 CUnbiasedSkewnessBasic statistic. Unbiased Skewness
 CUniformIntRandomFunctor< Engine >
 CUniformRandomFunctor< Engine >
 CUnstridedArrayTag
 CUserRangeHistogram< BinCount >Histogram where user provides bounds for linear range mapping from values to indices
 CVariableSelectionResult
 CVectorComponentAccessor< VECTORTYPE >Accessor for one component of a vector
 CVectorComponentValueAccessor< VECTORTYPE >Accessor for one component of a vector
 CVectorElementAccessor< ACCESSOR >Accessor for one component of a vector
 CVectorNormFunctor< ValueType >A functor for computing the vector norm
 CVectorNormSqFunctor< ValueType >A functor for computing the squared vector norm
 CVisitorBase
 CVisitorNode< Visitor, Next >
 CVolumeExportInfoArgument object for the function exportVolume()
 CVolumeImportInfoArgument object for the function importVolume()
 CWatershedOptionsOptions object for watershedsRegionGrowing()
 CWeightArg< INDEX >Specifies index of data in CoupledHandle
 CWeighted< A >Compute weighted version of the statistic
 CWignerMatrix< Real >Computation of Wigner D matrix + rotation functions in SH,VH and R³
 CXYZ2LabFunctor< T >Convert standardized tri-stimulus XYZ into perceptual uniform CIE L*a*b*
 CXYZ2LabFunctor< component_type >
 CXYZ2LuvFunctor< T >Convert standardized tri-stimulus XYZ into perceptual uniform CIE L*u*v*
 CXYZ2LuvFunctor< component_type >
 CXYZ2RGBFunctor< T >Convert standardized tri-stimulus XYZ into linear (raw) RGB
 CXYZ2RGBPrimeFunctor< T >Convert standardized tri-stimulus XYZ into non-linear (gamma corrected) R'G'B'
 CYPrimeCbCr2RGBPrimeFunctor< T >Convert Y'CbCr color difference components into non-linear (gamma corrected) R'G'B'
 CYPrimeIQ2RGBPrimeFunctor< T >Convert Y'IQ color components into non-linear (gamma corrected) R'G'B'
 CYPrimePbPr2RGBPrimeFunctor< T >Convert Y'PbPr color difference components into non-linear (gamma corrected) R'G'B'
 CYPrimeUV2RGBPrimeFunctor< T >Convert Y'UV color components into non-linear (gamma corrected) R'G'B'

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de)
Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

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vigra 1.9.0 (Sun Aug 10 2014)