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Class Hierarchy VIGRA

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 1234]
oCAbsPowerSum< N >Basic statistic. AbsPowerSum<N> = $ \sum_i |x_i|^N $
oCAccumulatorChain< T, Selected, dynamic >Create an accumulator chain containing the selected statistics and their dependencies
oCAccumulatorChain< CoupledArrays< N, T1, T2, T3, T4, T5 >::HandleType, Selected, dynamic >
oCAccumulatorChain< CoupledArrays< N, T1, T2, T3, T4, T5 >::HandleType, Selected, true >
oCAccumulatorChain< CoupledHandleType< N >::type, SELECT >
oCAccumulatorChain< CoupledHandleType< N, T >::type, SELECT >
oCAccumulatorChain< T, Selected, true >
oCAccumulatorChainArray< T, Selected, dynamic >Create an array of accumulator chains containing the selected per-region and global statistics and their dependencies
oCAccumulatorChainArray< CoupledArrays< N, T1, T2, T3, T4, T5 >::HandleType, Selected, dynamic >
oCAccumulatorChainArray< CoupledArrays< N, T1, T2, T3, T4, T5 >::HandleType, Selected, true >
oCAccumulatorChainArray< T, Selected, true >
oCAdjacencyListGraphUndirected adjacency list graph in the LEMON API
oCAffineMotionEstimationOptions< SPLINEORDER >Option object for affine registration functions
oCAnyTypesafe storage of arbitrary values
oCAdjacencyListGraph::ArcMap< T >Default arc map
oCArgMaxWeightBasic statistic. Data where weight assumes its maximal value
oCArgMinWeightBasic statistic. Data value where weight assumes its minimal value
oCArrayOfRegionStatistics< RegionStatistics, LabelType >Calculate statistics for all regions of a labeled image
oCArrayVectorView< T >
oCArrayVectorView< arc_descriptor >
oCArrayVectorView< ARITHTYPE >
oCArrayVectorView< ArrayVector< bool > >
oCArrayVectorView< ArrayVector< edge_descriptor > >
oCArrayVectorView< ArrayVector< MultiArrayIndex > >
oCArrayVectorView< AxisInfo >
oCArrayVectorView< BinType >
oCArrayVectorView< bool >
oCArrayVectorView< char >
oCArrayVectorView< ClassLabelType >
oCArrayVectorView< DecisionTree_t >
oCArrayVectorView< detail::DecisionTreeDeprec >
oCArrayVectorView< double >
oCArrayVectorView< hsize_t >
oCArrayVectorView< ImageType >
oCArrayVectorView< index_type >
oCArrayVectorView< IndexType >
oCArrayVectorView< int >
oCArrayVectorView< INT >
oCArrayVectorView< Int32 >
oCArrayVectorView< Label >
oCArrayVectorView< Label_t >
oCArrayVectorView< Matrix< Complex > >
oCArrayVectorView< MultiArrayIndex >
oCArrayVectorView< NeighborOffsetArray >
oCArrayVectorView< Node >
oCArrayVectorView< npy_intp >
oCArrayVectorView< Permutation< 1 > >
oCArrayVectorView< Permutation< N > >
oCArrayVectorView< POINT >
oCArrayVectorView< point_type >
oCArrayVectorView< RegionAccumulatorChain >
oCArrayVectorView< Segment >
oCArrayVectorView< shape_type >
oCArrayVectorView< SharedChunkHandle< N, T > * >
oCArrayVectorView< size_t >
oCArrayVectorView< std::pair< Int32, double > >
oCArrayVectorView< std::ptrdiff_t >
oCArrayVectorView< std::queue< ValueType > >
oCArrayVectorView< unsigned char >
oCArrayVectorView< vigra::ArrayVector< index_type > >
oCArrayVectorView< vigra::ArrayVector< typename out_edge_iterator::vigra::TinyVector > >
oCArrayVectorView< vigra::TinyVector >
oCAutoRangeHistogram< BinCount >Histogram where range mapping bounds are defined by minimum and maximum of data
oCBasicImage< PIXELTYPE, Alloc >Fundamental class template for images
oCBasicImage< double >
oCBasicImage< float >
oCBasicImage< InternalValue >
oCBasicImage< TinyVector< double, 2 > >
oCBasicImage< value_type >
oCBasicImage< VALUETYPE >
oCBasicImageIteratorBase< IMAGEITERATOR, PIXELTYPE, REFERENCE, POINTER, LINESTARTITERATOR >
oCBasicImageIteratorBase< BasicImageIterator< PIXELTYPE, ITERATOR >, PIXELTYPE, PIXELTYPE &, PIXELTYPE *, ITERATOR >
oCBasicImageIteratorBase< ConstBasicImageIterator< PIXELTYPE, ITERATOR >, PIXELTYPE, PIXELTYPE const &, PIXELTYPE const *, ITERATOR >
oCBasicImageView< PIXELTYPE >BasicImage using foreign memory
oCBestGiniOfColumn< LineSearchLossTag >
oCBestGiniOfColumn< vigra::GiniCriterion >
oCBilinearInterpolatingAccessor< ACCESSOR, VALUETYPE >Bilinear interpolation at non-integer positions
oCBinaryForestBinaryForest stores a collection of rooted binary trees
oCBlueAccessor< RGBVALUE >
oCBox< 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()
oCBox< PointValue, DIM >
oCBrightnessContrastFunctor< PixelType >Adjust brightness and contrast of an image
oCBrightnessContrastFunctor< ComponentType >
oCBrightnessContrastFunctor< unsigned char >
oCBSplineBase< ORDER, T >
oCBSplineBase< ORDER, double >
oCBucketQueue< ValueType, Ascending >Priority queue implemented using bucket sort
oCCatmullRomSpline< T >
oCCentral< A >Modifier. Substract mean before computing statistic
oCCentral< PowerSum< 2 > >Spezialization: works in pass 1, operator+=() supported (merging supported)
oCCentral< PowerSum< 3 > >Specialization: works in pass 2, operator+=() supported (merging supported)
oCCentral< PowerSum< 4 > >Specialization: works in pass 2, operator+=() supported (merging supported)
oCCentralMoment< N >Alias. CentralMoment<N>
oCChangeablePriorityQueue< T, COMPARE >Heap-based changable priority queue with a maximum number of elemements
oCChangeablePriorityQueue< ValueType >
oCChangeablePriorityQueue< WeightType >
oCChunkedArray< N, T >Interface and base class for chunked arrays
oCChunkedArrayOptionsOption object for ChunkedArray construction
oCChunkedArrayTag
oCcl_charNAccessor_COMP
oCcl_TYPE3WriteAccessor_s1
oCcl_TYPE3WriteAccessor_s2
oCClusteringOptionsOptions object for hierarchical clustering
oCColumnIterator< IMAGE_ITERATOR >Iterator adapter to linearly access columns
oCConstValueIterator< PIXELTYPE >Iterator that always returns the constant specified in the constructor
oCConvexHullCompute the convex hull of a region
oCConvexHullFeaturesCompute object features related to the convex hull
oCConvolutionOptions< dim >Options class template for convolutions
oCConvolutionOptions< DIM >
oCConvolutionOptions< N >
oCCoord< A >Modifier. Compute statistic from pixel coordinates rather than from pixel values
oCCoordinateConstValueAccessor< Accessor, COORD >Forward accessor to the value() part of the values an iterator points to
oCCoordinateSystemBasic statistic. Identity matrix of appropriate size
oCCorrectStatus
oCCoscotFunction< T >
oCCountingIterator< T >Iterator that counts upwards or downwards with a given step size
oCCoupledHandle< T, NEXT >
oCCoupledIteratorType< N, T1, T2, T3, T4, T5 >
oCCoupledScanOrderIterator< N, HANDLES, DIMENSION >Iterate over multiple images simultaneously in scan order
oCCoupledScanOrderIterator< N >
oCCrackContourCirculator< IMAGEITERATOR >Circulator that walks around a given region
oCDataArg< INDEX >Specifies index of data in CoupledHandle
oCDepthStopRandom forest 'maximum depth' stop criterion
oCDiff2DTwo dimensional difference vector
oCDiffusivityFunctor< Value >Diffusivity functor for non-linear diffusion
oCDist2D
oCDistancePowerFunctor< N >
oCDivideByCount< A >Modifier. Divide statistic by Count: DivideByCount<TAG> = TAG / Count
oCDivideUnbiased< A >Modifier. Divide statistics by Count-1: DivideUnbiased<TAG> = TAG / (Count-1)
oCDraw< T1, T2, C1, C2 >
oCDT_StackEntry< Iter >
oCDualVector< T, N >
oCEarlyStoppStdStandard early stopping criterion
oCEdgel
oCAdjacencyListGraph::EdgeMap< T >Default edge map
oCEdgeWeightNodeFeatures< MERGE_GRAPH, EDGE_INDICATOR_MAP, EDGE_SIZE_MAP, NODE_FEATURE_MAP, NODE_SIZE_MAP, MIN_WEIGHT_MAP, NODE_LABEL_MAP >This Cluster Operator is a MONSTER. It can really do a lot
oCEnhancedFrostFunctor< VALUETYPE >This function tries to reduce the speckle noise of an image by applying the Enhanced Frost filter
oCEnhancedLeeFunctor< VALUETYPE >This function tries to reduce the speckle noise of an image by applying the Enhanced Lee filter
oCEntropyCriterion
oCEntropyScoreFunctor that computes the entropy score
oCFFTWComplex< Real >Wrapper class for the FFTW complex types 'fftw_complex'
oCFFTWConvolvePlan< N, Real >
oCFFTWImaginaryAccessor< Real >
oCFFTWLogMagnitudeAccessor< Real >
oCFFTWMagnitudeAccessor< Real >
oCFFTWPhaseAccessor< Real >
oCFFTWPlan< N, Real >
oCFFTWRealAccessor< Real >
oCFFTWSquaredMagnitudeAccessor< Real >
oCFilterIterator< PREDICATE, ITER >This iterator creates a view of another iterator and skips elements that do not fulfill a given predicate
oCFindAverage< VALUETYPE >Find the average pixel value in an image or ROI
oCFindAverageAndVariance< VALUETYPE >Find the average pixel value and its variance in an image or ROI
oCFindBoundingRectangleCalculate the bounding rectangle of an ROI in an image
oCFindMinMax< VALUETYPE >Find the minimum and maximum pixel value in an image or ROI
oCFindROISize< VALUETYPE >Calculate the size of an ROI in an image
oCFindSum< VALUETYPE >Find the sum of the pixel values in an image or ROI
oCFirstSeenBasic statistic. First data value seen of the object
oCFixedPoint< IntBits, FractionalBits >
oCFixedPoint16< IntBits, OverflowHandling >
oCFlatScatterMatrixBasic statistic. Flattened uppter-triangular part of scatter matrix
oCFunctorTraits< T >Export associated information for a functor
oCGammaFunctor< PixelType >Perform gamma correction of an image
oCGammaFunctor< ComponentType >
oCGammaFunctor< unsigned char >
oCGammaMAPFunctor< VALUETYPE >This function tries to reduce the speckle noise of an image by applying the Gamma Maximum A Posteriori (MAP) filter
oCGaussian< T >
oCGeneralScorer< FUNCTOR >
oCGetClusterVariables
oCGiniCriterion
oCGiniScoreFunctor that computes the gini score
oCGlobal< A >Modifier. Compute statistic globally rather than per region
oCGlobalRangeHistogram< BinCount >Like AutoRangeHistogram, but use global min/max rather than region min/max
oCGrayToRGBAccessor< VALUETYPE >
oCGreenAccessor< RGBVALUE >
oCGridGraph< N, DirectedTag >Define a grid graph in arbitrary dimensions
oCGridGraph< N, undirected_tag >
oCHC_Entry
oCHClustering
oCHDF5DisableErrorOutputTemporarily disable HDF5's native error output
oCHDF5FileAccess to HDF5 files
oCHDF5HandleWrapper for unique hid_t objects
oCHDF5HandleSharedWrapper for shared hid_t objects
oCHDF5ImportInfoArgument object for the function readHDF5()
oCHierarchicalIteratorType< N, T1, T2, T3, T4, T5 >
oCHistogramOptionsSet histogram options
oCImageArray< ImageType, Alloc >Fundamental class template for arrays of equal-sized images
oCImageExportInfoArgument object for the function exportImage()
oCImageImportInfoArgument object for the function importImage()
oCImageIteratorBase< IMAGEITERATOR, PIXELTYPE, REFERENCE, POINTER, StridedOrUnstrided >Base class for 2D random access iterators
oCImageIteratorBase< ConstImageIterator< PIXELTYPE >, PIXELTYPE, PIXELTYPE const &, PIXELTYPE const * >
oCImageIteratorBase< ConstStridedImageIterator< PIXELTYPE >, PIXELTYPE, PIXELTYPE const &, PIXELTYPE const *, StridedArrayTag >
oCImageIteratorBase< ImageIterator< PIXELTYPE >, PIXELTYPE, PIXELTYPE &, PIXELTYPE * >
oCImageIteratorBase< StridedImageIterator< PIXELTYPE >, PIXELTYPE, PIXELTYPE &, PIXELTYPE *, StridedArrayTag >
oCImagePyramid< ImageType, Alloc >Class template for logarithmically tapering image pyramids
oCConvexHullFeatures::Impl< T, BASE >Result type of the covex hull feature calculation
oCGridGraph< N, DirectedTag >::InDegMapType of a property map that returns the number of incoming edges of a given node (API: LEMON, use via lemon::InDegMap<Graph>)
oCGridGraph< N, DirectedTag >::IndexMapType of a property map that returns the coordinate of a given node (API: LEMON)
oCIntegerHistogram< BinCount >Histogram where data values are equal to bin indices
oCIterablePartition< T >
oCIterablePartition< IdType >
oCIteratorAdaptor< Policy >Quickly create 1-dimensional iterator adapters
oCIteratorTraits< T >Export associated information for each image iterator
oCKernel1D< ARITHTYPE >Generic 1 dimensional convolution kernel
oCKernel2D< ARITHTYPE >Generic 2 dimensional convolution kernel
oCKolmogorovSmirnovScoreFunctor that computes the Kolmogorov-Smirnov score
oCKuanFunctor< VALUETYPE >This function tries to reduce the speckle noise of an image by applying the Kuan filter
oCKurtosisBasic statistic. Kurtosis
oCLab2RGBFunctor< T >Convert perceptual uniform CIE L*a*b* into linear (raw) RGB
oCLab2RGBPrimeFunctor< T >Convert perceptual uniform CIE L*a*b* into non-linear (gamma corrected) R'G'B'
oCLab2XYZFunctor< T >Convert perceptual uniform CIE L*a*b* into standardized tri-stimulus XYZ
oCLab2XYZFunctor< component_type >
oCLabelArg< INDEX >Specifies index of labels in CoupledHandle
oCLabelOptionsOption object for labelMultiArray()
oCLastValueFunctor< VALUETYPE >Stores and returns the last value it has seen
oCLeastAngleRegressionOptionsPass options to leastAngleRegression()
oCLeeFunctor< VALUETYPE >This function tries to reduce the speckle noise of an image by applying the basic Lee filter
oCLineIterator< IMAGE_ITERATOR >Iterator adapter to iterate along an arbitrary line on the image
oCLocalMinmaxOptionsOptions object for localMinima() and localMaxima()
oCLuv2RGBFunctor< T >Convert perceptual uniform CIE L*u*v* into linear (raw) RGB
oCLuv2RGBPrimeFunctor< T >Convert perceptual uniform CIE L*u*v* into non-linear (gamma corrected) R'G'B'
oCLuv2XYZFunctor< T >Convert perceptual uniform CIE L*u*v* into standardized tri-stimulus XYZ
oCLuv2XYZFunctor< component_type >
oCMagnitudeFunctor< ValueType >
oCMaximumBasic statistic. Maximum value
oCMedian
oCMergeGraphAdaptor< GRAPH >Undirected graph adaptor for edge contraction and feature merging
oCMeshGridAccessor
oCMetric< T >Functor to compute a metric between two vectors
oCMetric< float >
oCMinimumBasic statistic. Minimum value
oCMoment< N >Alias. Moment<N>
oCMultiArrayNavigator< 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
oCMultiArrayShape< N >
oCMultiArrayShape< 2 >
oCMultiArrayShape< actual_dimension >
oCMultiArrayShape< dim >
oCMultiArrayShape< Dimensions >
oCMultiArrayView< N, T, StrideTag >Base class for, and view to, vigra::MultiArray
oCMultiArrayView< 1, int >
oCMultiArrayView< 1, T >
oCMultiArrayView< 1, T, StridedArrayTag >
oCMultiArrayView< 2, double >
oCMultiArrayView< 2, int >
oCMultiArrayView< 2, LabelInt >
oCMultiArrayView< 2, T, C1 >
oCMultiArrayView< 2, T, C2 >
oCMultiArrayView< 2, T1, C1 >
oCMultiArrayView< 2, T2, C2 >
oCMultiArrayView< 2, UInt8 >
oCMultiArrayView< 2, VALUETYPE, StridedOrUnstrided >
oCMultiArrayView< DIM, PixelTypeIn >
oCMultiArrayView< DIM, RealPromotePixelType >
oCMultiArrayView< DIM, RealPromoteScalarType >
oCMultiArrayView< IntrinsicGraphShape< Graph >::IntrinsicEdgeMapDimension, Value >
oCMultiArrayView< IntrinsicGraphShape< Graph >::IntrinsicNodeMapDimension, Value >
oCMultiArrayView< N, NumpyArrayTraits< N, T, Stride >::value_type, Stride >
oCMultiArrayView< N, Real, UnstridedArrayTag >
oCMultiArrayView< N, T, S >
oCMultiArrayView< N, T, UnstridedArrayTag >
oCMultiArrayView< N, UnqualifiedType< U >::type >
oCMultiArrayView< N, vigra::detail::ResolveMultiband< T >::type, vigra::detail::ResolveMultiband< T >::Stride >
oCMultiBlocking< DIM, C >
oCMultiCoordinateNavigator< Dimensions, N >A navigator that provides access to the 1D subranges of an n-dimensional range given by an nD shape
oCMultiImageAccessor2< Iter1, Acc1, Iter2, Acc2 >Access two images simultaneously
oCMultiIterator< N, T, REFERENCE, POINTER >A multi-dimensional hierarchical iterator to be used with vigra::MultiArrayView if it is not strided
oCNeighborCodeEncapsulation of direction management for 4-neighborhood
oCNeighborCodeEncapsulation of direction management for the 8-neighborhood
oCNeighborCode3DEncapsulation of direction management of neighbors for a 3D 6-neighborhood
oCNeighborCode3DEncapsulation of direction management of neighbors for a 3D 26-neighborhood
oCNeighborhoodCirculator< IMAGEITERATOR, NEIGHBORCODE >Circulator that walks around a given location in a given image
oCNeighborhoodCirculator< IMAGEITERATOR, EightNeighborCode >
oCNeighborOffsetCirculator< NEIGHBORCODE >Circulator that walks around a given location
oCNodeBase
oCNodeComplexityStopRandom forest 'node complexity' stop criterion
oCAdjacencyListGraph::NodeMap< T >Default node map
oCNoiseNormalizationOptionsPass options to one of the noise normalization functions
oCNonlinearLSQOptionsPass options to nonlinearLeastSquares()
oCNormalizeStatus
oCNormalRandomFunctor< Engine >
oCNumInstancesStopRandom forest 'number of datapoints' stop criterion
oCNumpyAnyArray
oCGridGraph< N, DirectedTag >::OutDegMapType of a property map that returns the number of outgoing edges of a given node (API: LEMON, use via lemon::OutDegMap<Graph>)
oCParallelOptionsOption base class for parallel algorithms
oCPermuteCluster< Iter, DT >
oCPLSAOptionsOption object for the pLSA algorithm
oCPolynomialView< T >
oCPolytope< N, T >Represent an n-dimensional polytope
oCPolytope< N, double >
oCPowerSum< N >Basic statistic. PowerSum<N> = $ \sum_i x_i^N $
oCPrincipal< A >Modifier. Project onto PCA eigenvectors
oCPrincipal< CoordinateSystem >Specialization (covariance eigenvectors): works in pass 1, operator+=() supported (merging)
oCPrincipal< PowerSum< 2 > >Specialization (covariance eigenvalues): works in pass 1, operator+=() supported (merging)
oCPriorityQueue< ValueType, PriorityType, Ascending >Heap-based priority queue compatible to BucketQueue
oCProblemSpec< LabelType >Problem specification class for the random forest
oCProcessor< Tag, LabelType, T1, C1, T2, C2 >
oCProcessor< ClassificationTag, LabelType, T1, C1, T2, C2 >
oCProcessor< RegressionTag, LabelType, T1, C1, T2, C2 >
oCPropertyMap< KEYTYPE, MAPPEDTYPE, ContainerTag >The PropertyMap is used to store Node or Arc information of graphs
oCPropertyMap< KEYTYPE, MAPPEDTYPE, IndexVectorTag >Specialization of PropertyMap that stores the elements in a vector (size = number of stored elements). An additional index vector is needed for bookkeeping (size = max node id of stored elements)
oCPropertyMap< KEYTYPE, MAPPEDTYPE, VectorTag >Specialization of PropertyMap that stores the elements in a vector (size = max node id of stored elements)
oCPurityStopRandom forest 'node purity' stop criterion
oCQuaternion< ValueType >
oCRandomForest< LabelType, PreprocessorTag >Random forest version 2 (see also vigra::rf3::RandomForest for version 3)
oCRandomForest< FEATURES, LABELS, SPLITTESTS, ACCTYPE >Random forest version 3
oCRandomForestClassCounter< DataSource, CountArray >
oCRandomForestOptionsOptions class for vigra::rf3::RandomForest version 3
oCRandomForestOptionsOptions object for the random forest
oCRandomNumberGenerator< Engine >
oCRandomSplitOfColumn
oCRangeReturn both the minimum and maximum in std::pair
oCRational< IntType >
oCRect2DTwo dimensional rectangle
oCRedAccessor< RGBVALUE >
oCReduceFunctor< FUNCTOR, VALUETYPE >Apply a functor to reduce the dimensionality of an array
oCRegionCircularityCompute the circularity of a 2D region
oCRegionContourCompute the contour of a 2D region
oCRegionEccentricityCompute the eccentricity of a 2D region in terms of its prinipal radii
oCRegionPerimeterCompute the perimeter of a 2D region
oCRFErrorCallback
oCRFVisitorBaseBase class from which all random forest visitors derive
oCRFVisitorNode< VISITOR, NEXT, CPY >Container elements of the statically linked visitor list. Use the create_visitor() functions to create visitors up to size 10
oCRGB2LabFunctor< T >Convert linear (raw) RGB into perceptual uniform CIE L*a*b*
oCRGB2LuvFunctor< T >Convert linear (raw) RGB into perceptual uniform CIE L*u*v*
oCRGB2RGBPrimeFunctor< From, To >Convert linear (raw) RGB into non-linear (gamma corrected) R'G'B'
oCRGB2sRGBFunctor< From, To >Convert linear (raw) RGB into standardized sRGB
oCRGB2XYZFunctor< T >Convert linear (raw) RGB into standardized tri-stimulus XYZ
oCRGBGradientMagnitudeFunctor< ValueType >
oCRGBPrime2LabFunctor< T >Convert non-linear (gamma corrected) R'G'B' into perceptual uniform CIE L*a*b*
oCRGBPrime2LuvFunctor< T >Convert non-linear (gamma corrected) R'G'B' into perceptual uniform CIE L*u*v*
oCRGBPrime2RGBFunctor< From, To >Convert non-linear (gamma corrected) R'G'B' into non-linear (raw) RGB
oCRGBPrime2XYZFunctor< T >Convert non-linear (gamma corrected) R'G'B' into standardized tri-stimulus XYZ
oCRGBPrime2YPrimeCbCrFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'CbCr color difference components
oCRGBPrime2YPrimeIQFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'IQ components
oCRGBPrime2YPrimePbPrFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'PbPr color difference components
oCRGBPrime2YPrimeUVFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'UV components
oCRGBToGrayAccessor< RGBVALUE >
oCRootDivideByCount< A >Modifier. RootDivideByCount<TAG> = sqrt( TAG/Count )
oCRootDivideUnbiased< A >Modifier. RootDivideUnbiased<TAG> = sqrt( TAG / (Count-1) )
oCRowIterator< IMAGE_ITERATOR >Iterator adapter to linearly access row
oCSampler< Random >Create random samples from a sequence of indices
oCSamplerOptionsOptions object for the Sampler class
oCScatterMatrixEigensystem
oCSeedOptionsOptions object for generateWatershedSeeds()
oCSeedRgDirectValueFunctor< Value >Statistics functor to be used for seeded region growing
oCSelect< 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
oCShortestPathDijkstra< GRAPH, WEIGHT_TYPE >Shortest path computer
oCSIFImportInfoExtracts image properties from an Andor SIF file header
oCSkeletonOptionsOption object for skeletonizeImage()
oCSkewnessBasic statistic. Skewness
oCSlantedEdgeMTFOptionsPass options to one of the slantedEdgeMTF() functions
oCSlicOptionsOptions object for slicSuperpixels()
oCSortSamplesByDimensions< DataMatrix >
oCSplice< T >
oCSplineImageView< ORDER, VALUETYPE >Create a continuous view onto a discrete image using splines
oCSplineImageView0< VALUETYPE, INTERNAL_TRAVERSER >Create an image view for nearest-neighbor interpolation
oCSplineImageView0< VALUETYPE >
oCSplineImageView1< VALUETYPE, INTERNAL_TRAVERSER >Create an image view for bi-linear interpolation
oCSplineImageView1< VALUETYPE >
oCSplitBase< Tag >
oCsRGB2RGBFunctor< From, To >Convert standardized sRGB into non-linear (raw) RGB
oCStandardAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
oCStandardAccessor< RGBVALUE >
oCStandardAccessor< SEQUENCE >
oCStandardAccessor< VECTOR >
oCStandardConstAccessor< VALUETYPE >Encapsulate read access to the values an iterator points to
oCStandardConstValueAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
oCStandardQuantiles< Hist >Compute (0%, 10%, 25%, 50%, 75%, 90%, 100%) quantiles from given histogram
oCStandardValueAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
oCStopBase
oCStridedArrayTag
oCStridedMultiIterator< N, T, REFERENCE, POINTER >A multi-dimensional hierarchical iterator to be used with vigra::MultiArrayView if it is not strided
oCThinPlateSplineFunctor
oCThreadPoolThread pool class to manage a set of parallel workers
oCThreshold< SrcValueType, DestValueType >Threshold an image
oCTinyVectorBase< V1, SIZE, D1, D2 >Base class for fixed size vectors
oCTinyVectorBase< double, SIZE, double[SIZE], TinyVector< double, SIZE > >
oCTinyVectorBase< float, SIZE, float[SIZE], TinyVector< float, SIZE > >
oCTinyVectorBase< INDEX_TYPE, SIZE, INDEX_TYPE[SIZE], TinyVector< INDEX_TYPE, SIZE > >
oCTinyVectorBase< int, SIZE, int[SIZE], TinyVector< int, SIZE > >
oCTinyVectorBase< PointValue, SIZE, PointValue[SIZE], TinyVector< PointValue, SIZE > >
oCTinyVectorBase< T, SIZE, T *, TinyVectorView< T, SIZE > >
oCTinyVectorBase< T, SIZE, T[SIZE], TinyVector< T, SIZE > >
oCTinyVectorBase< unsigned int, SIZE, unsigned int[SIZE], TinyVector< unsigned int, SIZE > >
oCTinyVectorBase< ValueType, SIZE, ValueType[SIZE], TinyVector< ValueType, SIZE > >
oCTinyVectorBase< VALUETYPE, SIZE, VALUETYPE[SIZE], TinyVector< VALUETYPE, SIZE > >
oCGridGraph< N, DirectedTag >::traversal_categoryDefine several graph tags related to graph traversal (API: boost::graph, use via boost::graph_traits<Graph>::traversal_category)
oCUnbiasedKurtosisBasic statistic. Unbiased Kurtosis
oCUnbiasedSkewnessBasic statistic. Unbiased Skewness
oCUniformIntRandomFunctor< Engine >
oCUniformRandomFunctor< Engine >
oCUnstridedArrayTag
oCUserRangeHistogram< BinCount >Histogram where user provides bounds for linear range mapping from values to indices
oCVariableSelectionResult
oCVectorComponentAccessor< VECTORTYPE >Accessor for one component of a vector
oCVectorComponentValueAccessor< VECTORTYPE >Accessor for one component of a vector
oCVectorElementAccessor< ACCESSOR >Accessor for one component of a vector
oCVectorNormFunctor< ValueType >A functor for computing the vector norm
oCVectorNormSqFunctor< ValueType >A functor for computing the squared vector norm
oCVisitorBase
oCVisitorCopy< VISITOR >
oCVisitorNode< Visitor, Next >
oCVolumeExportInfoArgument object for the function exportVolume()
oCVolumeImportInfoArgument object for the function importVolume()
oCWatershedOptionsOptions object for watershed algorithms
oCWeightArg< INDEX >Specifies index of data in CoupledHandle
oCWeighted< A >Compute weighted version of the statistic
oCWignerMatrix< Real >Computation of Wigner D matrix + rotation functions in SH,VH and R³
oCXYZ2LabFunctor< T >Convert standardized tri-stimulus XYZ into perceptual uniform CIE L*a*b*
oCXYZ2LabFunctor< component_type >
oCXYZ2LuvFunctor< T >Convert standardized tri-stimulus XYZ into perceptual uniform CIE L*u*v*
oCXYZ2LuvFunctor< component_type >
oCXYZ2RGBFunctor< T >Convert standardized tri-stimulus XYZ into linear (raw) RGB
oCXYZ2RGBPrimeFunctor< T >Convert standardized tri-stimulus XYZ into non-linear (gamma corrected) R'G'B'
oCYPrimeCbCr2RGBPrimeFunctor< T >Convert Y'CbCr color difference components into non-linear (gamma corrected) R'G'B'
oCYPrimeIQ2RGBPrimeFunctor< T >Convert Y'IQ color components into non-linear (gamma corrected) R'G'B'
oCYPrimePbPr2RGBPrimeFunctor< 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 1.11.1 (Fri May 19 2017)