Commit 63a2f365 authored by Julien Michel's avatar Julien Michel

DOC: Update documentation to remove references to removed filters

parent b6a1d3fb
......@@ -36,7 +36,7 @@
// This example shows the basic approach to perform object based analysis on a image.
// The input image is firstly segmented using the \doxygen{otb}{MeanShiftSegmentationFilter}
// Then each segmented region is converted to a Map of labeled objects.
// Afterwards the \doxygen{otb}{otbMultiChannelRAndNIRIndexImageFilter} computes
// Afterwards the \doxygen{itk}{UnaryFunctorImageFilter} computes
// radiometric attributes for each object. In this example the NDVI is computed.
// The computed feature is passed to the \doxygen{otb}{BandsStatisticsAttributesLabelMapFilter}
// which computes statistics over the resulting band.
......
......@@ -36,7 +36,7 @@
//
//
// The following example illustrates the use of the
// \doxygen{otb}{MultiChannelRAndBAndNIRIndexImageFilter} with the
// \doxygen{itk}{UnaryFunctorImageFilter} with the
// use of the Atmospherically Resistant Vegetation Index (ARVI) \subdoxygen{otb}{Functor}{ARVI}. ARVI
// is an improved version of the NDVI that is more robust to the
// atmospheric effect. In addition to the red and NIR channels (used
......@@ -74,14 +74,6 @@
// \item \subdoxygen{otb}{Functor}{EVI}
// \end{itemize}
// With the \doxygen{otb}{MultiChannelRAndBAndNIRIndexImageFilter} class the
// input has to be a multi channel image and the user has to specify index channel
// of the red, blue and NIR channel.
//
// Let's look at the minimal code required to use this algorithm. First, the following header
// defining the \doxygen{otb}{MultiChannelRAndBAndNIRIndexImageFilter}
// class must be included.
#include "itkUnaryFunctorImageFilter.h"
#include "otbVegetationIndicesFunctor.h"
......@@ -125,7 +117,7 @@ int main(int argc, char* argv[])
typedef otb::Functor::ARVI<InputPixelType, InputPixelType, InputPixelType, OutputPixelType> FunctorType;
// The
// \doxygen{otb}{MultiChannelRAndBAndNIRIndexImageFilter}
// \doxygen{itk}{UnaryFunctorImageFilter}
// type is defined using the image types and the ARVI functor as
// template parameters. We then instantiate the filter itself.
......@@ -148,7 +140,7 @@ int main(int argc, char* argv[])
filter->GetFunctor().SetNIRIndex(::atoi(argv[7]));
// The $\gamma$ parameter is set. The
// \doxygen{otb}{MultiChannelRAndBAndNIRIndexImageFilter}
// \doxygen{otb::Functor}{ARVI}
// class sets the default value of $\gamma$ to $0.5$. This parameter
// is used to reduce the atmospheric effect on a global scale.
......
......@@ -38,7 +38,7 @@
//
//
// The following example illustrates the use of the
// otb::MultiChannelRAndGAndNIR VegetationIndexImageFilter with the
// itk::UnaryFunctorImageFilter with the
// use of the Angular Vegetation Index (AVI).
// The equation for the Angular Vegetation Index involves the gren, red
// and near infra-red bands. $\lambda_1$, $\lambda_2$ and $\lambda_3$ are the mid-band
......@@ -59,15 +59,9 @@
//
// For more details, refer to Plummer work \cite{AVI}.
//
// With the
// \doxygen{otb}{MultiChannelRAndGAndNIRIndexImageFilter}
// class the input has to be a multi channel image and the user has to
// specify the channel index of the red, green and NIR channel.
//
// Let's look at the minimal code required to use this
// algorithm. First, the following header defining the
// \doxygen{otb}{MultiChannelRAndGAndNIRIndexImageFilter}
// class must be included.
// algorithm.
#include "otbVegetationIndicesFunctor.h"
#include "itkUnaryFunctorImageFilter.h"
......
......@@ -40,8 +40,6 @@
0.020
*/
// \index{otb::MultiChannelRAndBAndNIRVegetationIndexImageFilter}
// \index{otb::MultiChannelRAndBAndNIRVegetationIndexImageFilter!header}
// \index{otb::VegetationIndex}
// \index{otb::VegetationIndex!header}
//
......
......@@ -29,12 +29,11 @@
*/
// \index{otb::RAndNIRIndexImageFilter}
// \index{otb::VegetationIndicesFunctor}
// \index{otb::VegetationIndicesFunctor!header}
//
// The following example illustrates the use of the
// \doxygen{otb}{RAndNIRIndexImageFilter} with the use of the Normalized
// \doxygen{itk}{BinaryFunctorImageFilter} with the use of the Normalized
// Difference Vegatation Index (NDVI).
// NDVI computes the difference between the NIR channel, noted $L_{NIR}$, and the red channel,
// noted $L_{r}$ radiances reflected from the surface and transmitted through the atmosphere:
......@@ -55,14 +54,8 @@
// \item \subdoxygen{otb}{Functor}{IPVI}
// \item \subdoxygen{otb}{Functor}{TNDVI}
// \end{itemize}
// With the \doxygen{otb}{RAndNIRIndexImageFilter} class the filter
// inputs are one channel images: one inmage represents the NIR channel, the
// the other the NIR channel.
//
// Let's look at the minimal code required to use this algorithm. First, the following header
// defining the \doxygen{otb}{RAndNIRIndexImageFilter}
// class must be included.
// Let's look at the minimal code required to use this algorithm.
#include "itkMacro.h"
#include "otbImage.h"
......@@ -100,7 +93,7 @@ int main(int argc, char* argv[])
// The NDVI (Normalized Difference Vegetation Index) is instantiated using
// the images pixel type as template parameters. It is
// implemented as a functor class which will be passed as a
// parameter to an \doxygen{otb}{RAndNIRIndexImageFilter}.
// parameter to an \doxygen{itk}{BinaryFunctorImageFilter}.
typedef otb::Functor::NDVI<InputPixelType, InputPixelType, OutputPixelType> FunctorType;
......
......@@ -66,14 +66,14 @@ int main(int argc, char* argv[])
typedef otb::Functor::LAIFromNDVIFormosat2Functor<InputImageType::InternalPixelType, InputImageType::InternalPixelType, OutputImageType::PixelType>
FunctorType;
typedef itk::UnaryFunctorImageFilter<InputImageType, OutputImageType, FunctorType> MultiChannelRAndNIRIndexImageFilterType;
typedef itk::UnaryFunctorImageFilter<InputImageType, OutputImageType, FunctorType> LAIFRomNDVIImageFilterType;
// Instantiating object
// Next the filter is created by invoking the \code{New()}~method and
// assigning the result to a \doxygen{itk}{SmartPointer}.
MultiChannelRAndNIRIndexImageFilterType::Pointer filter = MultiChannelRAndNIRIndexImageFilterType::New();
LAIFRomNDVIImageFilterType::Pointer filter = LAIFRomNDVIImageFilterType::New();
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer writer = WriterType::New();
......
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