Evaluate the MLC image from the Mueller image. More...

#include <otbMuellerToReciprocalCovarianceImageFilter.h>

Inheritance diagram for otb::Functor::MuellerToReciprocalCovarianceFunctor< TInput, TOutput >:

Public Types
typedef std::complex< double >	ComplexType
typedef TOutput::ValueType	OutputValueType

Public Member Functions
	MuellerToReciprocalCovarianceFunctor ()
virtual	~MuellerToReciprocalCovarianceFunctor ()
unsigned int	GetOutputSize ()
TOutput	operator() (const TInput &Mueller) const

Private Attributes
unsigned int	m_NumberOfComponentsPerPixel

Detailed Description

template<class TInput, class TOutput>
class otb::Functor::MuellerToReciprocalCovarianceFunctor< TInput, TOutput >

Evaluate the MLC image from the Mueller image.

Output value are:

channel #0 : $0.5*(M_{11} + M_{22} + 2*M_{12})$
channel #1 : $0.5*(M_{11} - M_{22})$
channel #2 : $0.5*(M_{11} + M_{22} - 2*M_{12})$
channel #3 : $0.5*(M_{13} + M_{23} + i*(M_{14}+M_{24}))$
channel #4 : $0.5*(M_{33} - M_{44} - 2*i*M_{34})$
channel #5 : $0.5*(M_{13} - M_{23} - i*(M_{14}-M_{24}))$

Where $M_{ij}$ are the coefficients of the input Mueller matrix.

Input pixel must have 10 channels (one for each Mueller matrix coeffcients). The order of the channels corresponds to : $\begin{pmatrix} {channel #0 }&{channel #1 }&{channel #2 }&{channel #3 } \\ {channel #4 }&{channel #5 }&{channel #6 }&{channel #7 } \\ {channel #8 }&{channel #9 }&{channel #10}&{channel #11} \\ {channel #12}&{channel #13}&{channel #14}&{channel #15} \\ \end{pmatrix}$

The output image has 6 channels : the diagonal and the upper element of the reciprocal matrix. Element are stored from left to right, line by line.

See also:: MuellerToCircularPolarisationImageFilter; MuellerToPolarisationDegreeAndPowerImageFilter

Definition at line 63 of file otbMuellerToReciprocalCovarianceImageFilter.h.