Module OTBUnmixing

Collaboration diagram for Module OTBUnmixing:

Classes
class	otb::Functor::ISRAUnmixingFunctor< TInput, TOutput, TPrecision >
class	otbMDMDNMFImageFilter
class	otb::SparseUnmixingImageFilter< TInputImage, TOutputImage, VNbInputImage, TPrecision, TMotherWaveletOperator >
class	otb::Functor::UnConstrainedLeastSquareFunctor< TInput, TOutput, TPrecision >

Typedefs
template<typename TInputImage , typename TOutputImage , typename TPrecision >
using	otb::ISRAUnmixingImageFilter = FunctorImageFilter< Functor::ISRAUnmixingFunctor< typename TInputImage::PixelType, typename TOutputImage::PixelType, TPrecision > >
template<typename TInputImage , typename TOutputImage , typename TPrecision >
using	otb::UnConstrainedLeastSquareImageFilter = FunctorImageFilter< Functor::UnConstrainedLeastSquareFunctor< typename TInputImage::PixelType, typename TOutputImage::PixelType, TPrecision > >

Detailed Description

Typedef Documentation

ISRAUnmixingImageFilter

template<typename TInputImage , typename TOutputImage , typename TPrecision >

otb::ISRAUnmixingImageFilter

Performs fully constrained least squares on each pixel of a VectorImage.

This filter takes as input a multiband image and a matrix. If the matrix is called , it solves, for each pixel , the system in the least square sense, with additional constraints on the solution ensuring positivity (each component is positive) and additivity (the sum of all components is 1).

The main use of this filter is to unmix an hyperspectral dataset, where is the mixing matrix, in which each row corresponds to an endmember signature.

The number of rows in must match the input image number of bands. The number of bands in the output image will be the number of columns of $A$

References "Fully Constrained Least-Squares Based Linear Unmixing." Daniel Heinz, Chein-I Chang, and Mark L.G. Althouse. IEEE. 1999.

Definition at line 119 of file otbISRAUnmixingImageFilter.h.

UnConstrainedLeastSquareImageFilter

template<typename TInputImage , typename TOutputImage , typename TPrecision >

otb::UnConstrainedLeastSquareImageFilter

Solves a least square system for each pixel.

This filter takes as input a multiband image and a matrix. If the matrix is called $A$, it solves, for each pixel $p$, the system in the least square sense, and saves the result in the output pixel.

It can be used as a simple way to unmix an hyperspectral dataset, where is the matrix in which each row corresponds to an endmember signature, although better algorithms can be found for this particular task.

The number of rows in must match the input image number of bands. The number of bands in the output image will be the number of columns of

Definition at line 96 of file otbUnConstrainedLeastSquareImageFilter.h.