te::rp::radar::MultiSourceClassifier Class Reference

Performs multi source image classification. More...

#include <MultiSourceClassifier.h>

Inheritance diagram for te::rp::radar::MultiSourceClassifier:

Public Types
typedef MultiSourceClassifierInputParameters	InputParameters
typedef MultiSourceClassifierOutputParameters	OutputParameters

Public Member Functions
bool	execute (te::rp::AlgorithmOutputParameters &outputParams)
	Executes the algorithm using the supplied parameters. More...
const std::string &	getErrorMessage () const
	Return the current error message if there is any. More...
bool	initialize (const te::rp::AlgorithmInputParameters &inputParams)
	Initialize the algorithm instance making it ready for execution. More...
bool	isInitialized () const
	Returns true if the algorithm instance is initialized and ready for execution. More...
	MultiSourceClassifier ()
void	reset ()
	Clear all internal allocated objects and reset the algorithm to its initial state. More...
	~MultiSourceClassifier ()

Protected Member Functions
void	setErrorMessage (const std::string &newErrorMessage)
	Set the current error message. More...

Protected Attributes
std::vector< unsigned int >	m_degreesOfFreedom
	Degrees of freedom container. More...
std::map< unsigned int, std::vector< std::vector< double > > >	m_distancesMaps
std::map< unsigned int, std::vector< std::vector< double > > >	m_imagesMaps
MultiSourceClassifier::InputParameters	m_inputParameters
	Input execution parameters. More...
bool	m_isInitialized
	Tells if this instance is initialized. More...
MultiSourceClassifier::OutputParameters	m_outputParameters
	Output execution parameters. More...
std::vector< std::vector< double > >	m_pValue
	P-values container. More...
std::vector< std::vector< double > >	m_statisticalTest
	Statistical tests container. More...
std::vector< std::vector< double > >	m_stochasticDistance
	Stochastic distances container. More...

Private Attributes
std::string	m_errorMessage
	Current error message. More...

Detailed Description

Performs multi source image classification.

Reference: B. C. Braga, C. d. C. Freitas and S. J. S. Sant'Anna, "Multisource classification based on uncertainty maps," 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, 2015, pp. 1630-1633, doi: 10.1109/IGARSS.2015.7326097.

Definition at line 52 of file MultiSourceClassifier.h.

Member Typedef Documentation

InputParameters

typedef MultiSourceClassifierInputParameters te::rp::radar::MultiSourceClassifier::InputParameters

Definition at line 55 of file MultiSourceClassifier.h.

OutputParameters

typedef MultiSourceClassifierOutputParameters te::rp::radar::MultiSourceClassifier::OutputParameters

Definition at line 56 of file MultiSourceClassifier.h.

Constructor & Destructor Documentation

MultiSourceClassifier()

te::rp::radar::MultiSourceClassifier::MultiSourceClassifier

(

)

~MultiSourceClassifier()

te::rp::radar::MultiSourceClassifier::~MultiSourceClassifier

(

)

Member Function Documentation

execute()

bool te::rp::radar::MultiSourceClassifier::execute ( te::rp::AlgorithmOutputParameters &  outputParams )

virtual

Executes the algorithm using the supplied parameters.

Parameters

outputParams

Output parameters.

Returns

true if OK, false on errors.

Note

A return error string can be obtained via Algorithm::getErrorMessage()

Implements te::rp::Algorithm.

getErrorMessage()

const std::string & te::rp::Algorithm::getErrorMessage ( ) const

inherited

Return the current error message if there is any.

Returns

Return the current error message if there is any.

initialize()

bool te::rp::radar::MultiSourceClassifier::initialize ( const te::rp::AlgorithmInputParameters &  inputParams )

virtual

Initialize the algorithm instance making it ready for execution.

Parameters

inputParams

Input parameters.

Returns

true if OK, false on errors.

Note

A return error string can be obtained via Algorithm::getErrorMessage()

Implements te::rp::Algorithm.

isInitialized()

bool te::rp::radar::MultiSourceClassifier::isInitialized ( ) const

virtual

Returns true if the algorithm instance is initialized and ready for execution.

Returns

true if the algorithm instance is initialized and ready for execution.

Implements te::rp::Algorithm.

reset()

void te::rp::radar::MultiSourceClassifier::reset ( )

virtual

Clear all internal allocated objects and reset the algorithm to its initial state.

Reimplemented from te::rp::Algorithm.

setErrorMessage()

void te::rp::Algorithm::setErrorMessage ( const std::string &  newErrorMessage )

protectedinherited

Set the current error message.

Parameters

newErrorMessage

New error message;

Member Data Documentation

m_degreesOfFreedom

std::vector< unsigned int > te::rp::radar::MultiSourceClassifier::m_degreesOfFreedom

protected

Degrees of freedom container.

Definition at line 89 of file MultiSourceClassifier.h.

m_distancesMaps

std::map< unsigned int, std::vector< std::vector< double > > > te::rp::radar::MultiSourceClassifier::m_distancesMaps

protected

Definition at line 93 of file MultiSourceClassifier.h.

m_errorMessage

std::string te::rp::Algorithm::m_errorMessage

privateinherited

Current error message.

Definition at line 104 of file Algorithm.h.

m_imagesMaps

std::map< unsigned int, std::vector< std::vector< double > > > te::rp::radar::MultiSourceClassifier::m_imagesMaps

protected

Definition at line 91 of file MultiSourceClassifier.h.

m_inputParameters

MultiSourceClassifier::InputParameters te::rp::radar::MultiSourceClassifier::m_inputParameters

protected

Input execution parameters.

Definition at line 77 of file MultiSourceClassifier.h.

m_isInitialized

bool te::rp::radar::MultiSourceClassifier::m_isInitialized

protected

Tells if this instance is initialized.

Definition at line 81 of file MultiSourceClassifier.h.

m_outputParameters

MultiSourceClassifier::OutputParameters te::rp::radar::MultiSourceClassifier::m_outputParameters

protected

Output execution parameters.

Definition at line 79 of file MultiSourceClassifier.h.

m_pValue

std::vector< std::vector< double > > te::rp::radar::MultiSourceClassifier::m_pValue

protected

P-values container.

Definition at line 87 of file MultiSourceClassifier.h.

m_statisticalTest

std::vector< std::vector< double > > te::rp::radar::MultiSourceClassifier::m_statisticalTest

protected

Statistical tests container.

Definition at line 85 of file MultiSourceClassifier.h.

m_stochasticDistance

std::vector< std::vector< double > > te::rp::radar::MultiSourceClassifier::m_stochasticDistance

protected

Stochastic distances container.

Definition at line 83 of file MultiSourceClassifier.h.

---

The documentation for this class was generated from the following file:

• /home/castejon/castejon_files/develop/terralib5/git_release/src/terralib/rp/radar/MultiSourceClassifier.h