diff --git a/Data/Baseline/OTB/Images/apTvUtSmoothingTestAnisotropic.tif b/Data/Baseline/OTB/Images/apTvUtSmoothingTestAnisotropic.tif
new file mode 100644
index 0000000000000000000000000000000000000000..5336d199981b5d04949f5975d7db85891472cc02
--- /dev/null
+++ b/Data/Baseline/OTB/Images/apTvUtSmoothingTestAnisotropic.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bdd0ce0f98ec479767e9e4cbb8f118753963f9a91c689870c3f02758de94d15e
+size 3422183
diff --git a/Data/Baseline/OTB/Images/apTvUtSmoothingTestGaussian.tif b/Data/Baseline/OTB/Images/apTvUtSmoothingTestGaussian.tif
new file mode 100644
index 0000000000000000000000000000000000000000..539c8486c84743e13cdaccf1c654fd11e3191975
--- /dev/null
+++ b/Data/Baseline/OTB/Images/apTvUtSmoothingTestGaussian.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5a9e56c55f2cb4f16ad31b762f1a38283c664d5570671fdf5f8a905f03a53a13
+size 3308861
diff --git a/Data/Input/apTvUtSmoothingTest_OutXML.xml b/Data/Input/apTvUtSmoothingTest_OutXML.xml
deleted file mode 100644
index 2f95025e38bfb54bf6b8d5d9accf3e91b02c62f4..0000000000000000000000000000000000000000
--- a/Data/Input/apTvUtSmoothingTest_OutXML.xml
+++ /dev/null
@@ -1,38 +0,0 @@
-<?xml version="1.0" ?>
-<OTB>
- <version>3.18</version>
- <build>18-05-2013</build>
- <platform>Linux</platform>
- <application>
- <name>Smoothing</name>
- <descr>Apply a smoothing filter to an image</descr>
- <doc>
- <name>Smoothing</name>
- <longdescr>This application applies smoothing filter to an image. Either gaussian, mean, or anisotropic diffusion are available.</longdescr>
- <authors>OTB-Team</authors>
- <limitations>None</limitations>
- <seealso> </seealso>
- <tags>
- <tag>Image Filtering</tag>
- </tags>
- </doc>
- <parameter mandatory="true">
- <key>in</key>
- <type>InputImage</type>
- <name>Input Image</name>
- <value>/home/rashad/repos/orfeo/OTB-Data/Input/poupees.tif</value>
- </parameter>
- <parameter mandatory="true">
- <key>out</key>
- <type>OutputImage</type>
- <name>Output Image</name>
- <value>/home/rashad/repos/orfeo/build/OTB_/test-build/Testing/Temporary/apTvUtSmoothingTest_OutXML.tif</value>
- </parameter>
- <parameter mandatory="true">
- <key>type</key>
- <type>Choice</type>
- <name>Smoothing Type</name>
- <value>mean</value>
- </parameter>
- </application>
-</OTB>
diff --git a/Modules/Applications/AppFiltering/app/otbFastNLMeans.cxx b/Modules/Applications/AppFiltering/app/otbFastNLMeans.cxx
index 3ed27ed028bfe43d0e1c27e626c9ab6d155125a3..c6e12f241bdadc42a6f1852289d111f78c37a4cb 100644
--- a/Modules/Applications/AppFiltering/app/otbFastNLMeans.cxx
+++ b/Modules/Applications/AppFiltering/app/otbFastNLMeans.cxx
@@ -59,7 +59,7 @@ private:
"This filter relies on integral images. Overflow may happen though the risk is limited "
" by OTB mechanism which process data by chunks.");
SetDocAuthors("OTB-Team");
- SetDocSeeAlso(" ");
+ SetDocSeeAlso("Smoothing");
AddDocTag(Tags::Filter);
// Parameter declarations
@@ -110,25 +110,25 @@ private:
void DoExecute() override
{
- // Get the input image
- ImageType::Pointer imIn = this->GetParameterFloatImage("in");
- float sigma = this->GetParameterFloat("sig");
- float cutoffDistance = this->GetParameterFloat("thresh");
- int halfPatchSize = this->GetParameterInt("patchradius");
- int halfSearchSize = this->GetParameterInt("searchradius");
- NLMeansFilterType::Pointer nlMeansFilter = NLMeansFilterType::New();
+ // Get the input parameters
+ const auto imIn = this->GetParameterFloatImage("in");
+ const auto sigma = this->GetParameterFloat("sig");
+ const auto cutoffDistance = this->GetParameterFloat("thresh");
+ const auto halfPatchSize = this->GetParameterInt("patchradius");
+ const auto halfSearchSize = this->GetParameterInt("searchradius");
+
+ auto nlMeansFilter = NLMeansFilterType::New();
+
nlMeansFilter->SetInput(imIn);
nlMeansFilter->SetSigma(sigma);
nlMeansFilter->SetHalfWindowSize(halfPatchSize);
nlMeansFilter->SetHalfSearchSize(halfSearchSize);
nlMeansFilter->SetCutOffDistance(cutoffDistance);
- m_FilterRef = nlMeansFilter;
SetParameterOutputImage("out", nlMeansFilter->GetOutput());
RegisterPipeline();
}
- itk::LightObject::Pointer m_FilterRef;
}; // end class
} // namespace Wrapper
diff --git a/Modules/Applications/AppFiltering/app/otbSmoothing.cxx b/Modules/Applications/AppFiltering/app/otbSmoothing.cxx
index f465172b66a2ad441e7c12888d917409785a1d89..4803bc7e934cfe09e825ea39c82f1d571284b718 100644
--- a/Modules/Applications/AppFiltering/app/otbSmoothing.cxx
+++ b/Modules/Applications/AppFiltering/app/otbSmoothing.cxx
@@ -62,11 +62,21 @@ private:
SetDocLongDescription(
"This application applies a smoothing filter to an "
- "image. Three methods can be used: a gaussian filter , a mean filter "
- ", or an anisotropic diffusion using the Perona-Malik algorithm.");
+ "image. Three methods can be used: a mean filter, a gaussian filter based on [1]"
+ ", or an anisotropic diffusion using the Perona-Malik algorithm [2].");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
- SetDocSeeAlso(" ");
+ SetDocSeeAlso("FastNLMeans \n"
+ "[1] Tony Lindeberg Discrete "
+ "Scale-Space Theory and the Scale-Space Primal Sketch. Dissertation. Royal "
+ "Institute of Technology, Stockholm, Sweden. May 1991 \n"
+ "[2] Pietro Perona and Jitendra Malik, "
+ "Scale-space and edge detection using anisotropic diffusion, "
+ "IEEE Transactions on Pattern Analysis Machine Intelligence, vol. 12, pp. 629-639, 1990. \n"
+ "itk::MeanImageFilter (mean mode)\n"
+ "itk::DiscreteGaussianImageFilter (gaussian mode)\n"
+ "itk::GradientAnisotropicDiffusionImageFilter (anidif mode)."
+ );
AddDocTag(Tags::Filter);
@@ -86,13 +96,21 @@ private:
AddChoice("type.gaussian", "Gaussian");
- AddParameter(ParameterType_Float, "type.gaussian.radius", "Radius");
- SetParameterDescription("type.gaussian.radius", "Standard deviation of the gaussian kernel used to filter the image");
- SetDefaultParameterFloat("type.gaussian.radius", 2.0);
- // TODO rename this parameter
+ AddParameter(ParameterType_Float, "type.gaussian.stdev", "Standard deviation");
+ SetParameterDescription("type.gaussian.stdev", "Standard deviation of the gaussian kernel used to filter the image");
+ SetDefaultParameterFloat("type.gaussian.stdev", 2.0);
- AddChoice("type.anidif", "Anisotropic Diffusion");
+ AddParameter(ParameterType_Float, "type.gaussian.maxerror", "Maximum error");
+ SetParameterDescription("type.gaussian.maxerror", "The algorithm will size the discrete kernel so that the error "
+ "resulting from truncation of the kernel is no greater than maxerror.");
+ SetDefaultParameterFloat("type.gaussian.maxerror", 0.01);
+
+ AddParameter(ParameterType_Int, "type.gaussian.maxwidth", "Maximum kernel width");
+ SetParameterDescription("type.gaussian.maxwidth", "Set the kernel to be no wider than maxwidth pixels, "
+ "even if type.gaussian.maxerror demands it.");
+ SetDefaultParameterInt("type.gaussian.maxwidth", 32);
+ AddChoice("type.anidif", "Anisotropic Diffusion");
AddParameter(ParameterType_Float, "type.anidif.timestep", "Time Step");
SetParameterDescription("type.anidif.timestep", "Time step that will be used to discretize the diffusion equation");
@@ -139,79 +157,79 @@ private:
void DoExecute() override
{
- GetLogger()->Debug("Entering DoExecute\n");
-
-
- FloatVectorImageType::Pointer inImage = GetParameterImage("in");
+ const auto inImage = GetParameterImage("in");
switch (GetParameterInt("type"))
{
case Smoothing_Mean:
{
- GetLogger()->Debug("Using mean");
+ otbAppLogINFO("Using mean smoothing");
typedef itk::MeanImageFilter<ImageType, ImageType> MeanFilterType;
typedef otb::PerBandVectorImageFilter<FloatVectorImageType, FloatVectorImageType, MeanFilterType> PerBandMeanFilterType;
- PerBandMeanFilterType::Pointer perBand = PerBandMeanFilterType::New();
+ auto perBand = PerBandMeanFilterType::New();
perBand->SetInput(inImage);
MeanFilterType::InputSizeType radius;
radius.Fill(GetParameterInt("type.mean.radius"));
perBand->GetFilter()->SetRadius(radius);
- perBand->UpdateOutputInformation();
- m_FilterRef = perBand;
+
SetParameterOutputImage("out", perBand->GetOutput());
+
+ RegisterPipeline();
}
break;
case Smoothing_Gaussian:
{
- GetLogger()->Debug("Using gaussian");
+ otbAppLogINFO("Using gaussian smoothing");
typedef itk::DiscreteGaussianImageFilter<ImageType, ImageType> DiscreteGaussianFilterType;
typedef otb::PerBandVectorImageFilter<FloatVectorImageType, FloatVectorImageType, DiscreteGaussianFilterType> PerBandDiscreteGaussianFilterType;
- PerBandDiscreteGaussianFilterType::Pointer perBand = PerBandDiscreteGaussianFilterType::New();
+ auto perBand = PerBandDiscreteGaussianFilterType::New();
perBand->SetInput(inImage);
- double radius = GetParameterFloat("type.gaussian.radius");
- double variance = radius * radius;
+ const auto stdev = GetParameterFloat("type.gaussian.stdev");
+ const auto variance = stdev * stdev;
+
perBand->GetFilter()->SetVariance(variance);
perBand->GetFilter()->SetUseImageSpacing(false);
- perBand->UpdateOutputInformation();
- m_FilterRef = perBand;
+ perBand->GetFilter()->SetMaximumError(GetParameterFloat("type.gaussian.maxerror"));
+ perBand->GetFilter()->SetMaximumKernelWidth(GetParameterInt("type.gaussian.maxwidth"));
+
SetParameterOutputImage("out", perBand->GetOutput());
+
+ RegisterPipeline();
}
break;
case Smoothing_Anisotropic:
{
- GetLogger()->Debug("Using anisotropic diffusion");
+ otbAppLogINFO("Using anisotropic diffusion smoothing");
typedef itk::GradientAnisotropicDiffusionImageFilter<ImageType, ImageType> GradientAnisotropicDiffusionFilterType;
typedef otb::PerBandVectorImageFilter<FloatVectorImageType, FloatVectorImageType, GradientAnisotropicDiffusionFilterType>
PerBandGradientAnisotropicDiffusionFilterType;
- PerBandGradientAnisotropicDiffusionFilterType::Pointer perBand = PerBandGradientAnisotropicDiffusionFilterType::New();
+ auto perBand = PerBandGradientAnisotropicDiffusionFilterType::New();
perBand->SetInput(inImage);
- const int aniDifNbIter = GetParameterInt("type.anidif.nbiter");
+ const auto aniDifNbIter = GetParameterInt("type.anidif.nbiter");
perBand->GetFilter()->SetNumberOfIterations(static_cast<unsigned int>(aniDifNbIter));
- const float aniDifTimeStep = GetParameterFloat("type.anidif.timestep");
+ const auto aniDifTimeStep = GetParameterFloat("type.anidif.timestep");
perBand->GetFilter()->SetTimeStep(static_cast<double>(aniDifTimeStep));
perBand->GetFilter()->SetConductanceParameter(GetParameterFloat("type.anidif.conductance"));
perBand->GetFilter()->SetUseImageSpacing(false);
- perBand->UpdateOutputInformation();
- m_FilterRef = perBand;
SetParameterOutputImage("out", perBand->GetOutput());
+
+ RegisterPipeline();
}
break;
}
}
-
- itk::LightObject::Pointer m_FilterRef;
};
}
}
diff --git a/Modules/Applications/AppFiltering/test/CMakeLists.txt b/Modules/Applications/AppFiltering/test/CMakeLists.txt
index 84ce8527671b5e9ecf1540dd0d80216297cfa707..73fad582ae6d2870150d37b95da902c6761882ed 100644
--- a/Modules/Applications/AppFiltering/test/CMakeLists.txt
+++ b/Modules/Applications/AppFiltering/test/CMakeLists.txt
@@ -20,9 +20,20 @@
otb_module_test()
#----------- Smoothing TESTS ----------------
+
+otb_test_application(NAME apTvUtSmoothingTest_OutXML
+ APP Smoothing
+ OPTIONS -in ${INPUTDATA}/poupees.tif
+ -out ${TEMP}/apTvUtSmoothingTest_OutXML.tif
+ -type mean
+ -outxml ${TEMP}/apTvUtSmoothingTest_OutXML.xml
+ VALID --compare-image ${NOTOL}
+ ${BASELINE}/apTvUtSmoothingTest.tif
+ ${TEMP}/apTvUtSmoothingTest_OutXML.tif)
+
otb_test_application(NAME apTvUtSmoothingTest_InXML
APP Smoothing
- OPTIONS -inxml ${INPUTDATA}/apTvUtSmoothingTest_OutXML.xml
+ OPTIONS -inxml ${TEMP}/apTvUtSmoothingTest_OutXML.xml
-in ${INPUTDATA}/poupees.tif
-out ${TEMP}/apTvUtSmoothingTest_InXML.tif
-type mean
@@ -30,24 +41,32 @@ otb_test_application(NAME apTvUtSmoothingTest_InXML
${BASELINE}/apTvUtSmoothingTest.tif
${TEMP}/apTvUtSmoothingTest_InXML.tif)
-otb_test_application(NAME apTvUtSmoothingTest
+set_tests_properties( apTvUtSmoothingTest_InXML
+ PROPERTIES DEPENDS apTvUtSmoothingTest_OutXML)
+
+otb_test_application(NAME apTvUtSmoothingTestGaussian
APP Smoothing
OPTIONS -in ${INPUTDATA}/poupees.tif
- -out ${TEMP}/apTvUtSmoothingTest.tif
- -type mean
+ -out ${TEMP}/apTvUtSmoothingTestGaussian.tif
+ -type gaussian
+ -type.gaussian.stdev 2.0
+ -type.gaussian.maxerror 0.1
+ -type.gaussian.maxwidth 64
VALID --compare-image ${NOTOL}
- ${BASELINE}/apTvUtSmoothingTest.tif
- ${TEMP}/apTvUtSmoothingTest.tif)
+ ${BASELINE}/apTvUtSmoothingTestGaussian.tif
+ ${TEMP}/apTvUtSmoothingTestGaussian.tif)
-otb_test_application(NAME apTvUtSmoothingTest_OutXML
+otb_test_application(NAME apTvUtSmoothingTestAnisotropic
APP Smoothing
OPTIONS -in ${INPUTDATA}/poupees.tif
- -out ${TEMP}/apTvUtSmoothingTest_OutXML.tif
- -type mean
- -outxml ${TEMP}/apTvUtSmoothingTest_OutXML.xml
- VALID --compare-image ${NOTOL}
- ${BASELINE}/apTvUtSmoothingTest.tif
- ${TEMP}/apTvUtSmoothingTest_OutXML.tif)
+ -out ${TEMP}/apTvUtSmoothingTestAnisotropic.tif
+ -type anidif
+ -type.anidif.timestep 0.125
+ -type.anidif.nbiter 10
+ -type.anidif.conductance 1.
+ VALID --compare-image ${EPSILON_6}
+ ${BASELINE}/apTvUtSmoothingTestAnisotropic.tif
+ ${TEMP}/apTvUtSmoothingTestAnisotropic.tif)
#----------- Contrast TESTS ----------------
@@ -115,7 +134,3 @@ otb_test_application(NAME nlMeansTest_base
${BASELINE}/GomaAvant_NLMeans.tif
${TEMP}/GomaAvant_NLMeans.tif)
-
-
-
-