Commit 3fac966a authored by Cédric Traizet's avatar Cédric Traizet
Browse files

ENH: add new application SpectralAngleClassification (only SAM mode is implemented at the moment)

parent 87b0c511
......@@ -38,3 +38,8 @@ otb_create_application(
SOURCES otbEndmemberNumberEstimation.cxx
LINK_LIBRARIES ${${otb-module}_LIBRARIES})
otb_create_application(
NAME SpectralAngleClassification
SOURCES otbSpectralAngleClassification.cxx
LINK_LIBRARIES ${${otb-module}_LIBRARIES})
/*
* Copyright (C) 2005-2019 Centre National d'Etudes Spatiales (CNES)
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "otbWrapperApplication.h"
#include "otbWrapperApplicationFactory.h"
#include "otbSpectralAngleFunctor.h"
#include "otbFunctorImageFilter.h"
namespace otb
{
namespace Wrapper
{
class SpectralAngleClassification : public Application
{
public:
/** Standard class typedefs. */
using Self = SpectralAngleClassification;
using Superclass = Application;
using Pointer = itk::SmartPointer<Self>;
using ConstPointer = itk::SmartPointer<const Self>;
/** Standard macro */
itkNewMacro(Self);
itkTypeMacro(SpectralAngleClassification, otb::Application);
using ValueType = float;
using ImageType = otb::VectorImage<ValueType>;
using PixelType = ImageType::PixelType;
using SAMFilterType = otb::FunctorImageFilter<otb::Functor::SpectralAngleMapperFunctor<PixelType, PixelType, PixelType>>;
private:
void DoInit() override
{
SetName("SpectralAngleClassification");
SetDescription("Classifies an image using a spectral angle measure.");
// Documentation
SetDocLongDescription("TODO");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
SetDocSeeAlso("VertexComponentAnalysis \n"
"Du, Yingzi & Chang, Chein-I & Ren, Hsuan & Chang, Chein-Chi & Jensen, James & D'Amico, Francis. (2004). "
"New Hyperspectral Discrimination Measure for Spectral Characterization. Optical Engineering - OPT ENG. 43."
" 1777-1786. 10.1117/1.1766301. ");
AddDocTag(Tags::Hyperspectral);
AddParameter(ParameterType_InputImage, "in", "Input Image Filename");
SetParameterDescription("in", "The hyperspectral data cube input");
AddParameter(ParameterType_InputImage, "ie", "Input endmembers");
SetParameterDescription("ie",
"The endmembers (estimated pure pixels) to "
"use for unmixing. Must be stored as a multispectral image, where "
"each pixel is interpreted as an endmember.");
AddParameter(ParameterType_OutputImage, "measure", "Output spectral angle values");
SetParameterDescription("measure",
"Output image containing for each pixel from the input image the computed measure relative to each endmember");
MandatoryOff("measure");
AddParameter(ParameterType_OutputImage, "out", "Output classified image");
SetParameterDescription("out",
"Output classified image.");
MandatoryOff("out");
AddParameter(ParameterType_Choice, "mode", "Measure used for classification");
SetParameterDescription("mode", "Measure used for classification");
MandatoryOff("mode");
AddChoice("mode.sam", "Spectral angle mapper");
SetParameterDescription("mode.sam", "Spectral angle mapper (SAM) measure.");
AddChoice("mode.sid", "Spectral information divergence");
SetParameterDescription("mode.sid", "Spectral information divergence (SID) measure.");
AddRAMParameter();
SetMultiWriting(true);
// Doc example parameter settings
SetDocExampleParameterValue("in", "cupriteSubHsi.tif");
SetDocExampleParameterValue("ie", "cupriteEndmembers.tif");
SetDocExampleParameterValue("out", "classification.tif");
SetDocExampleParameterValue("measure", "measure.tif");
SetDocExampleParameterValue("mode", "sam");
SetOfficialDocLink();
}
void DoUpdateParameters() override
{
// Nothing to do here : all parameters are independent
}
void DoExecute() override
{
auto inputEndmemberImage = GetParameterImage("ie");
inputEndmemberImage->Update();
itk::ImageRegionConstIterator<ImageType> it(inputEndmemberImage, inputEndmemberImage->GetLargestPossibleRegion());
std::vector<PixelType> endmembers;
for (it.GoToBegin(); !it.IsAtEnd(); ++it)
{
endmembers.push_back(it.Get());
}
auto SAMFilter = SAMFilterType::New();
SAMFilter->GetModifiableFunctor().SetReferencePixels(endmembers);
SAMFilter->SetInput(GetParameterImage("in"));
if (HasValue("measure"))
{
SetParameterOutputImage("measure", SAMFilter->GetOutput());
}
if (HasValue("out"))
{
// This lambda return the index of the minimum value in a pixel
auto minIndexLambda = [](PixelType const & pixel)
{
auto min = std::numeric_limits<ValueType>::max();
unsigned int res = 0;
for (unsigned int i = 0; i < pixel.Size(); i++)
{
if (pixel[i] < min)
{
min = pixel[i];
res = i;
}
}
return res;
};
auto classificationFilter = NewFunctorFilter(minIndexLambda);
classificationFilter->SetInput(SAMFilter->GetOutput());
SetParameterOutputImage("out", classificationFilter->GetOutput());
RegisterPipeline();
}
else
{
RegisterPipeline();
}
}
};
}
}
OTB_APPLICATION_EXPORT(otb::Wrapper::SpectralAngleClassification)
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