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Commit f6d4e7bb authored by Cédric Traizet's avatar Cédric Traizet
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Merge branch 'smoothing_app_enhancement' into 'develop' 

Smoothing application enhancement

Closes #1961

See merge request !673
parents 6c2850fc c0f61f42
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        Data/Input/apTvUtSmoothingTest_OutXML.xml deleted 100644 → 0
        View file @ 6c2850fc
        <?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>
        Modules/Applications/AppFiltering/app/otbFastNLMeans.cxx
        View file @ f6d4e7bb
        ......@@ -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
        ......
        Modules/Applications/AppFiltering/app/otbSmoothing.cxx
        View file @ f6d4e7bb
        ......@@ -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;
        };
        }
        }
        ......
        Modules/Applications/AppFiltering/test/CMakeLists.txt
        View file @ f6d4e7bb
        ......@@ -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)
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