otbLargeScaleMeanShift.cxx

/*
 * Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
 *
 * This file is part of Orfeo Toolbox
 *
 *     https://www.orfeo-toolbox.org/
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "otbWrapperCompositeApplication.h"
#include "otbWrapperApplicationFactory.h"

namespace otb
{
namespace Wrapper
{

/**
 * \class LargeScaleMeanShift
 *
 * \brief All-in-one application for the LSMS framework
 *
 * This application gathers the 4 steps of the large-scale MeanShift
 * segmentation framework.
 * 
 */
class LargeScaleMeanShift : public CompositeApplication
{
public:
  /** Standard class typedefs. */
  typedef LargeScaleMeanShift           Self;
  typedef CompositeApplication          Superclass;
  typedef itk::SmartPointer<Self>       Pointer;
  typedef itk::SmartPointer<const Self> ConstPointer;

/** Standard macro */
  itkNewMacro(Self);

  itkTypeMacro(LargeScaleMeanShift, otb::CompositeApplication);

private:
  void DoInit() override
    {
    SetName("LargeScaleMeanShift");
    SetDescription("Large-scale segmentation using MeanShift");

    // Documentation
    SetDocName("Large-Scale MeanShift");
    SetDocLongDescription("This application chains together the 4 steps of the "
      "MeanShit framework, that is the MeanShiftSmoothing [1], the "
      "LSMSSegmentation [2], the LSMSSmallRegionsMerging [3] and the "
      "LSMSVectorization [4].\n\n"
      "This application can be a preliminary step for an object-based analysis.\n\n"
      "It generates a vector data file containing the regions extracted with "
      "the MeanShift algorithm. The spatial and range radius parameters allow "
      "adapting the sensitivity of the algorithm depending on the image dynamic "
      "and resolution. There is a step to remove small regions whose size "
      "(in pixels) is less than the given 'minsize' parameter. These regions "
      "are merged to a similar neighbor region. In the output vectors, there "