25#ifndef __TERRALIB_RP_RADAR_INTERNAL_WISHARTMODEL_H
26#define __TERRALIB_RP_RADAR_INTERNAL_WISHARTMODEL_H
30#include "../../raster/Raster.h"
31#include "../../geometry/Polygon.h"
34#include <boost/numeric/ublas/matrix.hpp>
35#include <boost/math/distributions/chi_squared.hpp>
128 boost::numeric::ublas::matrix< WishartFeatureType >
checkCovarianceMatrix(boost::numeric::ublas::matrix< WishartFeatureType >);
Wishart model data manipulation.
double m_significanceLevel
The significance level.
double m_betaValue
Beta value for Renyi distance type.
bool LoadingSamples(void)
bool CalculatingSigmaClass(void)
unsigned int m_lagX
The horizontal correlation value.
std::map< ClassIDT, ClassSamplesContainerT > MClassesSamplesCT
Multi-classes samples container type definition.
double m_ENL
Equivalent Number Look type.
std::vector< std::vector< double > > m_stochasticDistance
Stochastic distance container.
WishartModel()
Constructor.
std::vector< unsigned int > m_classesIDT
Training class ID.
std::vector< std::vector< double > > m_statisticalTest
Statistical test container.
te::rst::Raster * m_inputRasterPtr
Input raster.
unsigned int m_vectorOrMatrixOrder
The lexicographic vector and covariance matrix order.
boost::numeric::ublas::matrix< WishartFeatureType > checkCovarianceMatrix(boost::numeric::ublas::matrix< WishartFeatureType >)
std::vector< ClassSampleT > ClassSamplesContainerT
Class samples container type definition.
~WishartModel()
Destructor.
unsigned int ClassIDT
Class ID type definiton.
unsigned int m_numberOfRows
Number of rows that all input rasters must have.
std::string m_stochasticDistanceType
The stochastic distance type definition.
std::string m_radarDataRepresentationType
The radar data representation container (covarianceMatrix,lexicographicVector).
bool CreatingCovarianceRaster(void)
std::vector< WishartFeatureType > ClassSampleT
Class sample type definition.
std::vector< int > m_numberOfSamples
std::vector< te::gm::Polygon > m_polygonSamplesT
Training samples polygons.
std::vector< te::gm::Polygon * > m_polygonsSegImage
Polygons of segmented image.
unsigned int m_numberOfColumns
Number of columns that all input rasters must have.
std::vector< double > m_regionsSize
Size of regions.
boost::shared_ptr< MClassesSamplesCT > MClassesSamplesCTPtr
A shared pointer to a multi classes samples container type definition.
std::vector< boost::numeric::ublas::matrix< WishartFeatureType > > m_sigmaRegionsParameterMatrix
Sigma regions parameter matrix.
bool GettingAttributes(void)
std::vector< unsigned int > m_inputRastersBands
Bands to process.
bool CalculatingSigmaRegion(void)
unsigned int m_lagY
The vertical correlation value.
std::vector< double > m_samplesSize
Size of sample containers.
MClassesSamplesCTPtr m_trainSamplesPtr
A shared pointer to a always-valid structure where training samples are stored.
std::vector< std::vector< double > > m_pValue
P-values container.
std::vector< unsigned int > m_classesIndex2ID
A class index ordered vector of classes IDs for Sigma parameter.
bool GettingCompleteSigmaMatrixes(void)
ClassSamplesContainerT m_sigmaRegionsParameter
Sigma regions parameter.
ClassSamplesContainerT m_sigmaClassesParameter
Sigma classes parameter.
std::vector< boost::numeric::ublas::matrix< WishartFeatureType > > m_sigmaClassesParameterMatrix
Sigma classes parameter matrix.
std::vector< std::vector< double > > m_polygonSamplesTNew
Training samples polygons.
An abstract class for raster data strucutures.
std::complex< double > WishartFeatureType
#define TERPEXPORT
You can use this macro in order to export/import classes and functions from this module.