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otbClassificationMapRegularization.cxx 7.86 KiB
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/*
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 * Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
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 *
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 * This file is part of Orfeo Toolbox
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 *
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 *     https://www.orfeo-toolbox.org/
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 *
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 * Licensed under the Apache License, Version 2.0 (the "License");
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 * you may not use this file except in compliance with the License.
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 * You may obtain a copy of the License at
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 *
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 *     http://www.apache.org/licenses/LICENSE-2.0
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 *
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 * Unless required by applicable law or agreed to in writing, software
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 * distributed under the License is distributed on an "AS IS" BASIS,
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 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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 * See the License for the specific language governing permissions and
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 * limitations under the License.
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 */
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// Wrappers
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#include "otbWrapperApplication.h"
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#include "otbWrapperApplicationFactory.h"
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// Majority Voting filter includes
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#include "otbNeighborhoodMajorityVotingImageFilter.h"
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namespace otb
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{
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namespace Wrapper
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{
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class ClassificationMapRegularization : public Application
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{
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public:
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  /** Standard class typedefs. */
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  typedef ClassificationMapRegularization            Self;
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  typedef Application                   Superclass;
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  typedef itk::SmartPointer<Self>       Pointer;
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  typedef itk::SmartPointer<const Self> ConstPointer;
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  /** Standard macro */
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  itkNewMacro(Self);
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  itkTypeMacro(ClassificationMapRegularization, otb::Application);
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  /** Filters typedef */
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  typedef UInt16ImageType IOLabelImageType;
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  // Neighborhood majority voting filter type
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  typedef otb::NeighborhoodMajorityVotingImageFilter<IOLabelImageType> NeighborhoodMajorityVotingFilterType;
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  // Binary ball Structuring Element type
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  typedef NeighborhoodMajorityVotingFilterType::KernelType StructuringType;
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  typedef StructuringType::RadiusType RadiusType;
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private:
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  void DoInit() override
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  {
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    SetName("ClassificationMapRegularization");
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    SetDescription("Filters the input labeled image using Majority Voting in a ball shaped neighbordhood");
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    SetDocName("Classification Map Regularization");
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    SetDocLongDescription(
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        "This application filters the input labeled image (with a maximal class label = 65535) using Majority Voting in a ball shaped neighbordhood."
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        "Majority Voting takes the more representative value of all the pixels identified by the ball shaped structuring element and then sets the center pixel to this majority label value.\n\n"
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"* NoData is the label of the NOT classified pixels in the input image. These input pixels keep their NoData label in the output image.\n\n" "* Pixels with more than 1 majority class are marked as Undecided if the parameter 'ip.suvbool == true', or keep their Original labels otherwise."); SetDocLimitations("The input image must be a single band labeled image (with a maximal class label = 65535). The structuring element radius must have a minimum value equal to 1 pixel. Please note that the Undecided value must be different from existing labels in the input labeled image."); SetDocAuthors("OTB-Team"); SetDocSeeAlso(""); AddDocTag(Tags::Learning); AddDocTag(Tags::Analysis); /** GROUP IO CLASSIFICATION */ AddParameter(ParameterType_Group,"io","Input and output images"); SetParameterDescription("io","This group of parameters allows setting input and output images for classification map regularization by Majority Voting."); AddParameter(ParameterType_InputImage, "io.in", "Input classification image"); SetParameterDescription( "io.in", "The input labeled image to regularize."); AddParameter(ParameterType_OutputImage, "io.out", "Output regularized image"); SetParameterDescription( "io.out", "The output regularized labeled image."); SetDefaultOutputPixelType( "io.out", ImagePixelType_uint8); AddParameter(ParameterType_Group,"ip","Regularization parameters"); SetParameterDescription("ip","This group allows setting parameters for classification map regularization by Majority Voting."); AddParameter(ParameterType_Int, "ip.radius", "Structuring element radius (in pixels)"); SetParameterDescription("ip.radius", "The radius of the ball shaped structuring element (in pixels)."); SetDefaultParameterInt("ip.radius", 1.0); AddParameter(ParameterType_Bool, "ip.suvbool", "Set tie pixels to undecided"); SetParameterDescription("ip.suvbool", "If true, set pixels with more than one majority class to an undecided value. If false, keep their original labels."); AddParameter(ParameterType_Int, "ip.nodatalabel", "Label for the NoData class"); SetParameterDescription("ip.nodatalabel", "Label for the NoData class. Such input pixels keep their NoData label in the output image."); SetDefaultParameterInt("ip.nodatalabel", 0.0); AddParameter(ParameterType_Int, "ip.undecidedlabel", "Label for the Undecided class"); SetParameterDescription("ip.undecidedlabel", "Label for the Undecided class."); SetDefaultParameterInt("ip.undecidedlabel", 0.0); AddParameter(ParameterType_Bool, "ip.onlyisolatedpixels", "Process isolated pixels only"); SetParameterDescription("ip.onlyisolatedpixels", "Only pixels whose label is unique in the neighbordhood will be processed."); AddParameter(ParameterType_Int, "ip.isolatedthreshold", "Threshold for isolated pixels"); SetParameterDescription("ip.isolatedthreshold", "Maximum number of neighbours with the same label as the center pixel to consider that it is an isolated pixel."); SetDefaultParameterInt("ip.isolatedthreshold", 1); AddRAMParameter(); // Doc example parameter settings SetDocExampleParameterValue("io.in", "clLabeledImageQB123_1.tif"); SetDocExampleParameterValue("io.out", "clLabeledImageQB123_1_CMR_r2_nodl_10_undl_7.tif"); SetDocExampleParameterValue("ip.radius", "2"); SetDocExampleParameterValue("ip.suvbool", "true"); SetDocExampleParameterValue("ip.onlyisolatedpixels", "true"); SetDocExampleParameterValue("ip.nodatalabel", "10"); SetDocExampleParameterValue("ip.undecidedlabel", "7"); SetOfficialDocLink(); } void DoUpdateParameters() override { // Nothing to do here: all parameters are independent }
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void DoExecute() override { // Majority Voting m_NeighMajVotingFilter = NeighborhoodMajorityVotingFilterType::New(); // Load input labeled image to regularize UInt16ImageType::Pointer inImage = GetParameterUInt16Image("io.in"); // Neighborhood majority voting filter settings RadiusType rad; rad[0] = GetParameterInt("ip.radius"); rad[1] = GetParameterInt("ip.radius"); StructuringType seBall; seBall.SetRadius(rad); seBall.CreateStructuringElement(); m_NeighMajVotingFilter->SetKernel(seBall); m_NeighMajVotingFilter->SetInput(inImage); m_NeighMajVotingFilter->SetLabelForNoDataPixels(GetParameterInt("ip.nodatalabel")); m_NeighMajVotingFilter->SetLabelForUndecidedPixels(GetParameterInt("ip.undecidedlabel")); // Set to Undecided label if NOT unique Majority Voting if (GetParameterInt("ip.suvbool")) { m_NeighMajVotingFilter->SetKeepOriginalLabelBool(false); } // Keep Original label value if NOT unique Majority Voting else { m_NeighMajVotingFilter->SetKeepOriginalLabelBool(true); } // Process isolated pixels only if (GetParameterInt("ip.onlyisolatedpixels")) { m_NeighMajVotingFilter->SetOnlyIsolatedPixels(true); m_NeighMajVotingFilter->SetIsolatedThreshold(GetParameterInt("ip.isolatedthreshold")); } else { m_NeighMajVotingFilter->SetOnlyIsolatedPixels(false); } /** REGULARIZATION OF CLASSIFICATION */ SetParameterOutputImage<IOLabelImageType>("io.out", m_NeighMajVotingFilter->GetOutput()); }// END DoExecute() NeighborhoodMajorityVotingFilterType::Pointer m_NeighMajVotingFilter; }; // END class ClassificationMapRegularization }// END namespace wrapper }// END namespace otb OTB_APPLICATION_EXPORT(otb::Wrapper::ClassificationMapRegularization)