From b9524112ecde7c5c157c0d9fb13970e59bd233ad Mon Sep 17 00:00:00 2001
From: Cedric <cedric.traizet@c-s.fr>
Date: Wed, 9 Jan 2019 17:43:02 +0100
Subject: [PATCH] ENH: added the endmember number estimation to the application
---
.../app/otbEndmemberNumberEstimation.cxx | 27 ++++++++++++++++++-
1 file changed, 26 insertions(+), 1 deletion(-)
diff --git a/Modules/Applications/AppHyperspectral/app/otbEndmemberNumberEstimation.cxx b/Modules/Applications/AppHyperspectral/app/otbEndmemberNumberEstimation.cxx
index 2123ea15af..ef27cb2ba4 100644
--- a/Modules/Applications/AppHyperspectral/app/otbEndmemberNumberEstimation.cxx
+++ b/Modules/Applications/AppHyperspectral/app/otbEndmemberNumberEstimation.cxx
@@ -22,6 +22,8 @@
#include "otbWrapperApplicationFactory.h"
#include "otbStreamingStatisticsVectorImageFilter.h"
+#include "otbEigenvalueLikelihoodMaximisation.h"
+#include "otbVirtualDimensionality.h"
namespace otb
{
@@ -44,6 +46,8 @@ public:
typedef otb::StreamingStatisticsVectorImageFilter<FloatVectorImageType, float>
StreamingStatisticsVectorImageFilterType;
+ typedef otb::VirtualDimensionality<float> VirtualDimensionalityType;
+ typedef otb::EigenvalueLikelihoodMaximisation<float> EigenvalueLikelihoodMaximisationType;
private:
void DoInit() override
@@ -70,7 +74,7 @@ private:
AddChoice("algo.vd", "vd");
SetParameterDescription("algo.vd", "virtual dimensionality");
- AddParameter(ParameterType_String,"number","Number of endmembers");
+ AddParameter(ParameterType_Int,"number","Number of endmembers");
SetParameterDescription("number", "Estimated number of endmembers");
SetParameterRole("number", Role_Output);
@@ -92,6 +96,27 @@ private:
statisticsFilter->SetInput(GetParameterImage("in"));
statisticsFilter->Update();
+ int numberOfEndmembers = 0;
+ const std::string algorithm = GetParameterString("algo");
+ if (algorithm=="elm")
+ {
+ auto elm = EigenvalueLikelihoodMaximisationType::New();
+ elm->SetCovariance(statisticsFilter->GetCovariance().GetVnlMatrix());
+ elm->SetCorrelation(statisticsFilter->GetCorrelation().GetVnlMatrix());
+ elm->SetNumberOfPixels(GetParameterImage("in")->GetLargestPossibleRegion().GetNumberOfPixels());
+ elm->Compute();
+ numberOfEndmembers = elm->GetNumberOfEndmembers();
+ }
+ else if (algorithm=="vd")
+ {
+ auto vd = VirtualDimensionalityType::New();
+ vd->SetCovariance(statisticsFilter->GetCovariance().GetVnlMatrix());
+ vd->SetCorrelation(statisticsFilter->GetCorrelation().GetVnlMatrix());
+ vd->SetNumberOfPixels(GetParameterImage("in")->GetLargestPossibleRegion().GetNumberOfPixels());
+ vd->Compute();
+ numberOfEndmembers = vd->GetNumberOfEndmembers();
+ }
+ SetParameterInt("number", numberOfEndmembers);
}
};
--
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