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Class List VIGRA

Here are the classes, structs, unions and interfaces with brief descriptions:
AbsPowerSum< N >Basic statistic. AbsPowerSum<N> = $ \sum_i |x_i|^N $
AccumulatorChain< T, Selected, dynamic >Create an accumulator chain containing the selected statistics and their dependencies
AccumulatorChainArray< T, Selected, dynamic >Create an array of accumulator chains containing the selected per-region and global statistics and their dependencies
ArgMaxWeightBasic statistic. Data where weight assumes its maximal value
ArgMinWeightBasic statistic. Data value where weight assumes its minimal value
ArrayOfRegionStatistics< RegionStatistics, LabelType >Calculate statistics for all regions of a labeled image
ArrayVector< T, Alloc >
ArrayVectorView< T >
AutoRangeHistogram< BinCount >Histogram where range mapping bounds are defined by minimum and maximum of data
BasicImage< PIXELTYPE, Alloc >Fundamental class template for images
BasicImageIterator< PIXELTYPE, ITERATOR >
BasicImageIteratorBase< IMAGEITERATOR, PIXELTYPE, REFERENCE, POINTER, LINESTARTITERATOR >
BasicImageView< PIXELTYPE >BasicImage using foreign memory
BestGiniOfColumn< LineSearchLossTag >
BilinearInterpolatingAccessor< ACCESSOR, VALUETYPE >Bilinear interpolation at non-integer positions
BlueAccessor< RGBVALUE >
Box< 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()
BrightnessContrastFunctor< PixelType >Adjust brightness and contrast of an image
BSpline< ORDER, T >
BSplineBase< ORDER, T >
BucketQueue< ValueType, Ascending >Priority queue implemented using bucket sort
CatmullRomSpline< T >
Central< TAG >Modifier. Substract mean before computing statistic
Central< PowerSum< 2 > >Spezialization: works in pass 1, operator+=() supported (merging supported)
Central< PowerSum< 3 > >Specialization: works in pass 2, operator+=() supported (merging supported)
Central< PowerSum< 4 > >Specialization: works in pass 2, operator+=() supported (merging supported)
cl_charNAccessor_COMP
cl_TYPE3WriteAccessor_s1
cl_TYPE3WriteAccessor_s2
ClusterImportanceVisitor
ColumnIterator< IMAGE_ITERATOR >Iterator adapter to linearly access columns
CompleteOOBInfo
ConstBasicImageIterator< PIXELTYPE, ITERATOR >
ConstImageIterator< PIXELTYPE >Standard 2D random access const iterator for images that store the data as a linear array
ConstStridedImageIterator< PIXELTYPE >Const iterator to be used when pixels are to be skipped
ConstValueIterator< PIXELTYPE >Iterator that always returns the constant specified in the constructor
ConvolutionOptions< dim >Options class template for convolutions
Coord< TAG >Modifier. Compute statistic from pixel coordinates rather than from pixel values
CoordinateConstValueAccessor< Accessor, COORD >Forward accessor to the value() part of the values an iterator points to
CoordinateSystemBasic statistic. Identity matrix of appropriate size
CorrectStatus
CorrelationVisitor
CoscotFunction< T >
CoupledHandle< T, NEXT >
CoupledIteratorType< N, T1, T2, T3, T4, T5 >
CoupledScanOrderIterator< N, HANDLES, DIMENSION >Iterate over multiple images simultaneously in scan order
CrackContourCirculator< IMAGEITERATOR >Circulator that walks around a given region
DataArg< INDEX >Specifies index of data in CoupledHandle
Diff2DTwo dimensional difference vector
DiffusivityFunctor< Value >Diffusivity functor for non-linear diffusion
Dist2D
DivideByCount< TAG >Modifier. Divide statistic by Count: DivideByCount<TAG> = TAG / Count
DivideUnbiased< TAG >Modifier. Divide statistics by Count-1: DivideUnbiased<TAG> = TAG / (Count-1)
Draw< T1, T2, C1, C2 >
DT_StackEntry< Iter >
DynamicAccumulatorChain< T, Selected >Create a dynamic accumulator chain containing the selected statistics and their dependencies
DynamicAccumulatorChainArray< T, Selected >Create an array of dynamic accumulator chains containing the selected per-region and global statistics and their dependencies
EarlyStoppStdStandard early stopping criterion
Edgel
EntropyCriterion
FFTWComplex< Real >Wrapper class for the FFTW complex types 'fftw_complex'
FFTWConvolvePlan< N, Real >
FFTWImaginaryAccessor< Real >
FFTWMagnitudeAccessor< Real >
FFTWPhaseAccessor< Real >
FFTWPlan< N, Real >
FFTWRealAccessor< Real >
FFTWSquaredMagnitudeAccessor< Real >
FFTWWriteRealAccessor< Real >
FindAverage< VALUETYPE >Find the average pixel value in an image or ROI
FindAverageAndVariance< VALUETYPE >Find the average pixel value and its variance in an image or ROI
FindBoundingRectangleCalculate the bounding rectangle of an ROI in an image
FindMinMax< VALUETYPE >Find the minimum and maximum pixel value in an image or ROI
FindROISize< VALUETYPE >Calculate the size of an ROI in an image
FindSum< VALUETYPE >Find the sum of the pixel values in an image or ROI
FixedPoint< IntBits, FractionalBits >
FixedPoint16< IntBits, OverflowHandling >
FlatScatterMatrixBasic statistic. Flattened uppter-triangular part of scatter matrix
FunctorTraits< T >Export associated information for a functor
GaborFilterFamily< ImageType, Alloc >Family of gabor filters of different scale and direction
GammaFunctor< PixelType >Perform gamma correction of an image
Gaussian< T >
GetClusterVariables
GiniCriterion
Global< TAG >Modifier. Compute statistic globally rather than per region
GlobalRangeHistogram< BinCount >Like AutoRangeHistogram, but use global min/max rather than region min/max
GrayToRGBAccessor< VALUETYPE >
GreenAccessor< RGBVALUE >
HC_Entry
HClustering
HDF5FileAccess to HDF5 files
HDF5HandleWrapper for hid_t objects
HDF5ImportInfoArgument object for the function readHDF5()
HistogramOptionsSet histogram options
ImageArray< ImageType, Alloc >Fundamental class template for arrays of equal-sized images
ImageExportInfoArgument object for the function exportImage()
ImageImportInfoArgument object for the function importImage()
ImageIterator< PIXELTYPE >Standard 2D random access iterator for images that store the data in a linear array
ImageIteratorBase< IMAGEITERATOR, PIXELTYPE, REFERENCE, POINTER, StridedOrUnstrided >Base class for 2D random access iterators
ImagePyramid< ImageType, Alloc >Class template for logarithmically tapering image pyramids
IntegerHistogram< BinCount >Histogram where data values are equal to bin indices
IteratorAdaptor< Policy >Quickly create 1-dimensional iterator adapters
IteratorTraits< T >Export associated information for each image iterator
Kernel1D< ARITHTYPE >Generic 1 dimensional convolution kernel
Kernel2D< ARITHTYPE >Generic 2 dimensional convolution kernel
KurtosisBasic statistic. Kurtosis
Lab2RGBFunctor< T >Convert perceptual uniform CIE L*a*b* into linear (raw) RGB
Lab2RGBPrimeFunctor< T >Convert perceptual uniform CIE L*a*b* into non-linear (gamma corrected) R'G'B'
Lab2XYZFunctor< T >Convert perceptual uniform CIE L*a*b* into standardized tri-stimulus XYZ
LabelArg< INDEX >Specifies index of labels in CoupledHandle
LastValueFunctor< VALUETYPE >Stores and returns the last value it has seen
LeastAngleRegressionOptionsPass options to leastAngleRegression()
LineIterator< IMAGE_ITERATOR >Iterator adapter to iterate along an arbitrary line on the image
LocalMinmaxOptionsOptions object for localMinima() and localMaxima()
Luv2RGBFunctor< T >Convert perceptual uniform CIE L*u*v* into linear (raw) RGB
Luv2RGBPrimeFunctor< T >Convert perceptual uniform CIE L*u*v* into non-linear (gamma corrected) R'G'B'
Luv2XYZFunctor< T >Convert perceptual uniform CIE L*u*v* into standardized tri-stimulus XYZ
MagnitudeFunctor< ValueType >
MappedBucketQueue< ValueType, PriorityFunctor, Ascending >Priority queue implemented using bucket sort (STL compatible)
Matrix< T, ALLOC >
MaximumBasic statistic. Maximum value
Median
MeshGridAccessor
MinimumBasic statistic. Minimum value
MultiArray< N, T, A >Main MultiArray class containing the memory management
MultiArrayNavigator< 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
MultiArrayShape< N >
MultiArrayView< N, T, StrideTag >Base class for, and view to, vigra::MultiArray
MultiCoordinateNavigator< Dimensions, N >A navigator that provides access to the 1D subranges of an n-dimensional range given by an nD shape
MultiImageAccessor2< Iter1, Acc1, Iter2, Acc2 >Access two images simultaneously
MultiIterator< N, T, REFERENCE, POINTER >A multi-dimensional hierarchical iterator to be used with vigra::MultiArrayView if it is not strided
NeighborCodeEncapsulation of direction management for 4-neighborhood
NeighborCodeEncapsulation of direction management for the 8-neighborhood
NeighborCode3DEncapsulation of direction management of neighbors for a 3D 6-neighborhood
NeighborCode3DEncapsulation of direction management of neighbors for a 3D 26-neighborhood
NeighborhoodCirculator< IMAGEITERATOR, NEIGHBORCODE >Circulator that walks around a given location in a given image
NeighborOffsetCirculator< NEIGHBORCODE >Circulator that walks around a given location
Node< e_ConstProbNode >
NodeBase
NoiseNormalizationOptionsPass options to one of the noise normalization functions
NormalizeStatus
NormalRandomFunctor< Engine >
NumpyAnyArray
NumpyArray< N, T, Stride >
OnlineLearnVisitor
OOB_Error
OOB_PerTreeError
PermuteCluster< Iter, DT >
PLSAOptionsOption object for the pLSA algorithm
Point2DTwo dimensional point or position
Polynomial< T >
PolynomialView< T >
PowerSum< N >Basic statistic. PowerSum<N> = $ \sum_i x_i^N $
Principal< TAG >Modifier. Project onto PCA eigenvectors
Principal< CoordinateSystem >Specialization (covariance eigenvectors): works in pass 1, operator+=() supported (merging)
Principal< PowerSum< 2 > >Specialization (covariance eigenvalues): works in pass 1, operator+=() supported (merging)
PriorityQueue< ValueType, PriorityType, Ascending >Heap-based priority queue compatible to BucketQueue
ProblemSpec< LabelType >Problem specification class for the random forest
Processor< ClassificationTag, LabelType, T1, C1, T2, C2 >
Processor< RegressionTag, LabelType, T1, C1, T2, C2 >
Quaternion< ValueType >
RandomForest< LabelType, PreprocessorTag >
RandomForestClassCounter< DataSource, CountArray >
RandomForestOptionsOptions object for the random forest
RandomForestProgressVisitor
RandomNumberGenerator< Engine >
RandomSplitOfColumn
Rational< IntType >
Rect2DTwo dimensional rectangle
RedAccessor< RGBVALUE >
ReduceFunctor< FUNCTOR, VALUETYPE >Apply a functor to reduce the dimensionality of an array
RestrictedNeighborhoodCirculator< IMAGEITERATOR, NEIGHBORCODE >Circulator that walks around a given location in a given image, using a restricted neighborhood
RFErrorCallback
RGB2LabFunctor< T >Convert linear (raw) RGB into perceptual uniform CIE L*a*b*
RGB2LuvFunctor< T >Convert linear (raw) RGB into perceptual uniform CIE L*u*v*
RGB2RGBPrimeFunctor< From, To >Convert linear (raw) RGB into non-linear (gamma corrected) R'G'B'
RGB2sRGBFunctor< From, To >Convert linear (raw) RGB into standardized sRGB
RGB2XYZFunctor< T >Convert linear (raw) RGB into standardized tri-stimulus XYZ
RGBAccessor< RGBVALUE >
RGBGradientMagnitudeFunctor< ValueType >
RGBPrime2LabFunctor< T >Convert non-linear (gamma corrected) R'G'B' into perceptual uniform CIE L*a*b*
RGBPrime2LuvFunctor< T >Convert non-linear (gamma corrected) R'G'B' into perceptual uniform CIE L*u*v*
RGBPrime2RGBFunctor< From, To >Convert non-linear (gamma corrected) R'G'B' into non-linear (raw) RGB
RGBPrime2XYZFunctor< T >Convert non-linear (gamma corrected) R'G'B' into standardized tri-stimulus XYZ
RGBPrime2YPrimeCbCrFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'CbCr color difference components
RGBPrime2YPrimeIQFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'IQ components
RGBPrime2YPrimePbPrFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'PbPr color difference components
RGBPrime2YPrimeUVFunctor< T >Convert non-linear (gamma corrected) R'G'B' into Y'UV components
RGBToGrayAccessor< RGBVALUE >
RGBValue< VALUETYPE, RED_IDX, GREEN_IDX, BLUE_IDX >Class for a single RGB value
RootDivideByCount< TAG >Modifier. RootDivideByCount<TAG> = sqrt( TAG/Count )
RootDivideUnbiased< TAG >Modifier. RootDivideUnbiased<TAG> = sqrt( TAG / (Count-1) )
RowIterator< IMAGE_ITERATOR >Iterator adapter to linearly access row
Sampler< Random >Create random samples from a sequence of indices
SamplerOptionsOptions object for the Sampler class
ScatterMatrixEigensystem
SeedOptionsOptions object for generateWatershedSeeds()
SeedRgDirectValueFunctor< Value >Statistics functor to be used for seeded region growing
Select< 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
SequenceAccessor< SEQUENCE >Accessor for items that are STL compatible sequences
SIFImportInfoExtracts image properties from an Andor SIF file header
Size2DTwo dimensional size object
SkewnessBasic statistic. Skewness
SlantedEdgeMTFOptionsPass options to one of the slantedEdgeMTF() functions
SortSamplesByDimensions< DataMatrix >
Splice< T >
SplineImageView< ORDER, VALUETYPE >Create a continuous view onto a discrete image using splines
SplineImageView0< VALUETYPE, INTERNAL_TRAVERSER >Create an image view for nearest-neighbor interpolation
SplineImageView1< VALUETYPE, INTERNAL_TRAVERSER >Create an image view for bi-linear interpolation
SplitBase< Tag >
sRGB2RGBFunctor< From, To >Convert standardized sRGB into non-linear (raw) RGB
StandardAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
StandardConstAccessor< VALUETYPE >Encapsulate read access to the values an iterator points to
StandardConstValueAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
StandardQuantiles< HistogramAccumulator >Compute (0%, 10%, 25%, 50%, 75%, 90%, 100%) quantiles from given histogram
StandardValueAccessor< VALUETYPE >Encapsulate access to the values an iterator points to
StaticPolynomial< MAXORDER, T >
StopAfterTree
StopAfterVoteCount
StopBase
StopIfBinTest
StopIfConverging
StopIfMargin
StopIfProb
StopVisiting
StridedArrayTag
StridedImageIterator< PIXELTYPE >Iterator to be used when pixels are to be skipped
StridedMultiIterator< N, T, REFERENCE, POINTER >A multi-dimensional hierarchical iterator to be used with vigra::MultiArrayView if it is not strided
StridedScanOrderIterator< N, T, REFERENCE, POINTER, M >Sequential iterator for MultiArrayView
Threshold< SrcValueType, DestValueType >Threshold an image
ThresholdSplit< ColumnDecisionFunctor, Tag >
TinyVector< T, SIZE >Class for fixed size vectors.This class contains an array of size SIZE of the specified VALUETYPE. The interface conforms to STL vector, except that there are no functions that change the size of a TinyVector
TinyVectorBase< VALUETYPE, SIZE, DATA, DERIVED >Base class for fixed size vectors
TinyVectorView< T, SIZE >Wrapper for fixed size vectors
UnbiasedKurtosisBasic statistic. Unbiased Kurtosis
UnbiasedSkewnessBasic statistic. Unbiased Skewness
UniformIntRandomFunctor< Engine >
UniformRandomFunctor< Engine >
UnstridedArrayTag
UserRangeHistogram< BinCount >Histogram where user provides bounds for linear range mapping from values to indices
VariableImportanceVisitor
VariableSelectionResult
VectorAccessor< VECTOR >Accessor for items that are STL compatible vectors
VectorComponentAccessor< VECTORTYPE >Accessor for one component of a vector
VectorComponentValueAccessor< VECTORTYPE >Accessor for one component of a vector
VectorElementAccessor< ACCESSOR >Accessor for one component of a vector
VectorNormFunctor< ValueType >A functor for computing the vector norm
VectorNormSqFunctor< ValueType >A functor for computing the squared vector norm
VisitorBase
VisitorNode< Visitor, Next >
VolumeExportInfoArgument object for the function exportVolume()
VolumeImportInfoArgument object for the function importVolume()
WatershedOptionsOptions object for watershedsRegionGrowing()
WeightArg< INDEX >Specifies index of data in CoupledHandle
Weighted< TAG >Compute weighted version of the statistic
WignerMatrix< Real >Computation of Wigner D matrix + rotation functions in SH,VH and R³
XYZ2LabFunctor< T >Convert standardized tri-stimulus XYZ into perceptual uniform CIE L*a*b*
XYZ2LuvFunctor< T >Convert standardized tri-stimulus XYZ into perceptual uniform CIE L*u*v*
XYZ2RGBFunctor< T >Convert standardized tri-stimulus XYZ into linear (raw) RGB
XYZ2RGBPrimeFunctor< T >Convert standardized tri-stimulus XYZ into non-linear (gamma corrected) R'G'B'
YPrimeCbCr2RGBPrimeFunctor< T >Convert Y'CbCr color difference components into non-linear (gamma corrected) R'G'B'
YPrimeIQ2RGBPrimeFunctor< T >Convert Y'IQ color components into non-linear (gamma corrected) R'G'B'
YPrimePbPr2RGBPrimeFunctor< T >Convert Y'PbPr color difference components into non-linear (gamma corrected) R'G'B'
YPrimeUV2RGBPrimeFunctor< 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

html generated using doxygen and Python
vigra 1.9.0 (Tue Nov 6 2012)