From 3487572643d4a568fe1a5eb74acce8f79a82b370 Mon Sep 17 00:00:00 2001
From: Cedric <cedric.traizet@c-s.fr>
Date: Thu, 10 Jan 2019 11:35:55 +0100
Subject: [PATCH] ENH: code factorization
---
.../app/otbEndmemberNumberEstimation.cxx | 28 ++++++++++++-------
1 file changed, 18 insertions(+), 10 deletions(-)
diff --git a/Modules/Applications/AppHyperspectral/app/otbEndmemberNumberEstimation.cxx b/Modules/Applications/AppHyperspectral/app/otbEndmemberNumberEstimation.cxx
index 0ab2645baa..5413b925cd 100644
--- a/Modules/Applications/AppHyperspectral/app/otbEndmemberNumberEstimation.cxx
+++ b/Modules/Applications/AppHyperspectral/app/otbEndmemberNumberEstimation.cxx
@@ -122,30 +122,38 @@ private:
void DoExecute() override
{
- otbAppLogINFO("Computing statistics on input image");
+ // Load input image
+ auto inputImage = GetParameterImage("in");
+
+ otbAppLogINFO("Computing statistics on input image ...");
auto statisticsFilter = StreamingStatisticsVectorImageFilterType::New();
- statisticsFilter->SetInput(GetParameterImage("in"));
+ statisticsFilter->SetInput(inputImage);
statisticsFilter->Update();
+
+ auto correlationMatrix = statisticsFilter->GetCorrelation().GetVnlMatrix();
+ auto covarianceMatrix = statisticsFilter->GetCovariance().GetVnlMatrix();
+ auto numberOfPixels = inputImage->GetLargestPossibleRegion().GetNumberOfPixels();
+
int numberOfEndmembers = 0;
const std::string algorithm = GetParameterString("algo");
if (algorithm=="elm")
{
- otbAppLogINFO("Estimation algorithm : Eigenvalue Likelihood Maximization");
+ otbAppLogINFO("Estimation algorithm : Eigenvalue Likelihood Maximization.");
auto elm = EigenvalueLikelihoodMaximisationType::New();
- elm->SetCovariance(statisticsFilter->GetCovariance().GetVnlMatrix());
- elm->SetCorrelation(statisticsFilter->GetCorrelation().GetVnlMatrix());
- elm->SetNumberOfPixels(GetParameterImage("in")->GetLargestPossibleRegion().GetNumberOfPixels());
+ elm->SetCovariance(covarianceMatrix);
+ elm->SetCorrelation(correlationMatrix);
+ elm->SetNumberOfPixels(numberOfPixels);
elm->Compute();
numberOfEndmembers = elm->GetNumberOfEndmembers();
}
else if (algorithm=="vd")
{
- otbAppLogINFO("Estimation algorithm : Virtual Dimensionality");
+ otbAppLogINFO("Estimation algorithm : Virtual Dimensionality.");
auto vd = VirtualDimensionalityType::New();
- vd->SetCovariance(statisticsFilter->GetCovariance().GetVnlMatrix());
- vd->SetCorrelation(statisticsFilter->GetCorrelation().GetVnlMatrix());
- vd->SetNumberOfPixels(GetParameterImage("in")->GetLargestPossibleRegion().GetNumberOfPixels());
+ vd->SetCovariance(covarianceMatrix);
+ vd->SetCorrelation(correlationMatrix);
+ vd->SetNumberOfPixels(numberOfPixels);
vd->SetFAR(GetParameterFloat("algo.vd.far"));
vd->Compute();
numberOfEndmembers = vd->GetNumberOfEndmembers();
--
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