File: otbStreamingStatisticsMosaicFilter.h

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/*
 * Copyright (C) 1999-2011 Insight Software Consortium
 * Copyright (C) 2005-2020 Centre National d'Etudes Spatiales (CNES)
 * Copyright (C) 2016-2019 IRSTEA
 *
 * 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.
 */
#ifndef __StreamingStatisticsMosaicFilter_H
#define __StreamingStatisticsMosaicFilter_H

#include "otbStreamingMosaicFilterBase.h"
#include "otbPersistentMosaicFilter.h"
#include "otbPersistentFilterStreamingDecorator.h"
#include "itkArray.h"
#include "itkSimpleDataObjectDecorator.h"
#include "itkImageRegionConstIteratorWithOnlyIndex.h"

namespace otb
{
/** \class PersistentStatisticsMosaicFilter
 * \brief Computes the statistics of a mosaic from an input images set.
 * The output pixel value is equal to the number of overlaps
 *
 * Support streaming
 *
 * The pixels must support the operator ==, +, /, etc.
 * The "no data value", output spacing, interpolator can be chosen.
 * The behavior of the filter is to compute input images statistics
 * as they were in a layered fashion: interpolators are used to
 * compute pixels values of all input images for a given output pixel.
 * This is used to compute the following matrices: mean, standard
 * deviation, min, max, and means of pixels products. Let's denote
 * X one of these matrices, then X\{ij} is the statistic of the image
 * i in the overlapping area with the image j.
 *
 * \ingroup OTBMosaic
 * \ingroup OTBStatistics
 */
template <class TInputImage, class TOutputImage = TInputImage, class TInternalValueType = double>
class ITK_EXPORT PersistentStatisticsMosaicFilter : public otb::PersistentMosaicFilter<TInputImage, TOutputImage, TInternalValueType>
{
public:
  /** Standard Self typedef */
  typedef PersistentStatisticsMosaicFilter Self;
  typedef PersistentMosaicFilter<TInputImage, TOutputImage, TInternalValueType> Superclass;
  typedef itk::SmartPointer<Self>       Pointer;
  typedef itk::SmartPointer<const Self> ConstPointer;

  /** Method for creation through the object factory. */
  itkNewMacro(Self);

  /** Runtime information support. */
  itkTypeMacro(PersistentStatisticsMosaicFilter, PersistentMosaicFilter);

  /** Input image typedefs.  */
  typedef typename Superclass::InputImageType              InputImageType;
  typedef typename Superclass::InputImagePointer           InputImagePointer;
  typedef typename Superclass::InputImagePointType         InputImagePointType;
  typedef typename Superclass::InputImagePixelType         InputImagePixelType;
  typedef typename Superclass::InputImageInternalPixelType InputImageInternalPixelType;

  /** Output image typedefs.  */
  typedef typename Superclass::OutputImageType       OutputImageType;
  typedef typename Superclass::OutputImagePointType  OutputImagePointType;
  typedef typename Superclass::OutputImageRegionType OutputImageRegionType;

  /** Internal computing typedef support. */
  typedef typename Superclass::InternalValueType       InternalValueType;
  typedef typename Superclass::InterpolatorPointerType InterpolatorPointerType;

  typedef itk::ImageRegionConstIteratorWithOnlyIndex<OutputImageType> IteratorType;

  /** Typedefs for statistics */
  typedef vnl_vector<InternalValueType>                      RealVectorType;
  typedef vnl_matrix<InternalValueType>                      RealMatrixType;
  typedef itk::SimpleDataObjectDecorator<RealMatrixType>     RealMatrixObjectType;
  typedef std::vector<RealMatrixType>                        RealMatrixListType;
  typedef itk::SimpleDataObjectDecorator<RealMatrixListType> RealMatrixListObjectType;

  /** Smart Pointer type to a DataObject. */
  typedef typename itk::DataObject::Pointer                  DataObjectPointer;
  typedef itk::ProcessObject::DataObjectPointerArraySizeType DataObjectPointerArraySizeType;

  /** Overrided methods */
  void AllocateOutputs() override;
  void ThreadedGenerateData(const OutputImageRegionType& outputRegionForThread, itk::ThreadIdType threadId) override;
  void Reset() override;
  void Synthetize() override;

  /** Make a DataObject of the correct type to be used as the specified output. */
  DataObjectPointer MakeOutput(DataObjectPointerArraySizeType idx) override;
  using Superclass::MakeOutput;

  /** Return the computed Mean. */
  RealMatrixListType GetMeans() const
  {
    return this->GetMeansOutput()->Get();
  }
  RealMatrixListObjectType*       GetMeansOutput();
  const RealMatrixListObjectType* GetMeansOutput() const;

  /** Return the computed Std. */
  RealMatrixListType GetStds() const
  {
    return this->GetStdsOutput()->Get();
  }
  RealMatrixListObjectType*       GetStdsOutput();
  const RealMatrixListObjectType* GetStdsOutput() const;

  /** Return the computed Min. */
  RealMatrixListType GetMins() const
  {
    return this->GetMinsOutput()->Get();
  }
  RealMatrixListObjectType*       GetMinsOutput();
  const RealMatrixListObjectType* GetMinsOutput() const;

  /** Return the computed Max. */
  RealMatrixListType GetMaxs() const
  {
    return this->GetMaxsOutput()->Get();
  }
  RealMatrixListObjectType*       GetMaxsOutput();
  const RealMatrixListObjectType* GetMaxsOutput() const;

  /** Return the computed MeansOfProduct. */
  RealMatrixListType GetMeansOfProducts() const
  {
    return this->GetMeansOfProductsOutput()->Get();
  }
  RealMatrixListObjectType*       GetMeansOfProductsOutput();
  const RealMatrixListObjectType* GetMeansOfProductsOutput() const;

  /** Return the computed areas. */
  RealMatrixType GetAreas() const
  {
    return this->GetAreasOutput()->Get();
  }
  RealMatrixObjectType*       GetAreasOutput();
  const RealMatrixObjectType* GetAreasOutput() const;

protected:
  PersistentStatisticsMosaicFilter();
  virtual ~PersistentStatisticsMosaicFilter()
  {
  }

  /** Class for storing thread results:
   * -sum of values
   * -sum of squared values
   * -min value
   * -max value
   * -count
   */
  class ThreadResultsContainer
  {
  public:
    /** Default constructor */
    ThreadResultsContainer()
    {
    }

    /* Constructor with size */
    ThreadResultsContainer(unsigned int nbOfBands, unsigned int nbOfSamples)
    {
      Clear(nbOfBands, nbOfSamples);
    }

    /* Copy constructor */
    ThreadResultsContainer(const ThreadResultsContainer& other)
    {
      m_count = RealVectorType(other.m_count);
      m_sum   = RealMatrixType(other.m_sum);
      m_cosum = RealMatrixType(other.m_cosum);
      m_sqSum = RealMatrixType(other.m_sqSum);
      m_min   = RealMatrixType(other.m_min);
      m_max   = RealMatrixType(other.m_max);
    }

    /* Clear routine: Resize at the specified dimension and clear values */
    void Clear(unsigned int nbOfBands, unsigned int nbOfSamples)
    {
      const InternalValueType zeroValue = itk::NumericTraits<InternalValueType>::Zero;
      const InternalValueType supValue  = itk::NumericTraits<InternalValueType>::max();
      const InternalValueType infValue  = itk::NumericTraits<InternalValueType>::NonpositiveMin();

      m_count = RealVectorType(nbOfSamples, 0);
      m_sum   = RealMatrixType(nbOfBands, nbOfSamples, zeroValue);
      m_cosum = RealMatrixType(nbOfBands, nbOfSamples, zeroValue);
      m_sqSum = RealMatrixType(nbOfBands, nbOfSamples, zeroValue);
      m_min   = RealMatrixType(nbOfBands, nbOfSamples, supValue);
      m_max   = RealMatrixType(nbOfBands, nbOfSamples, infValue);
    }

    /* 1-Pixel update */
    void Update(const InputImagePixelType& pixel, unsigned int sampleId)
    {
      unsigned int nbOfBands = pixel.Size();

      m_count[sampleId]++;
      for (unsigned int band = 0; band < nbOfBands; band++)
      {
        // Cast
        InternalValueType pixelValue = static_cast<InternalValueType>(pixel[band]);

        // Update Min & max
        if (pixelValue < m_min[band][sampleId])
          m_min[band][sampleId] = pixelValue;
        if (pixelValue > m_max[band][sampleId])
          m_max[band][sampleId] = pixelValue;

        // Update Sums
        m_sum[band][sampleId] += pixelValue;
        m_sqSum[band][sampleId] += pixelValue * pixelValue;
      }
    }

    /* 2-Pixels update */
    void Update(const InputImagePixelType& pixel_i, const InputImagePixelType& pixel_j, unsigned int sampleId)
    {
      Update(pixel_i, sampleId);
      unsigned int nbOfBands = pixel_i.Size();
      for (unsigned int band = 0; band < nbOfBands; band++)
      {
        // Cast
        InternalValueType pixelValue_i = static_cast<InternalValueType>(pixel_i[band]);
        InternalValueType pixelValue_j = static_cast<InternalValueType>(pixel_j[band]);

        m_cosum[band][sampleId] += pixelValue_i * pixelValue_j;
      }
    }

    /* Self update */
    void Update(const ThreadResultsContainer& other)
    {
      unsigned int nbOfBands   = other.m_sum.rows();
      unsigned int nbOfSamples = other.m_sum.cols();

      for (unsigned int sampleId = 0; sampleId < nbOfSamples; sampleId++)
      {
        m_count[sampleId] += other.m_count[sampleId];
        for (unsigned int band = 0; band < nbOfBands; band++)
        {
          m_sum[band][sampleId] += other.m_sum[band][sampleId];
          m_cosum[band][sampleId] += other.m_cosum[band][sampleId];
          m_sqSum[band][sampleId] += other.m_sqSum[band][sampleId];
          if (other.m_min[band][sampleId] < m_min[band][sampleId])
            m_min[band][sampleId] = other.m_min[band][sampleId];
          if (other.m_max[band][sampleId] > m_max[band][sampleId])
            m_max[band][sampleId] = other.m_max[band][sampleId];
        }
      }
    }

    RealMatrixType m_sum;
    RealMatrixType m_sqSum;
    RealMatrixType m_cosum;
    RealMatrixType m_min;
    RealMatrixType m_max;
    RealVectorType m_count;
  };

  // Internal threads count
  std::vector<ThreadResultsContainer> m_InternalThreadResults;

  // Results
  RealMatrixListType m_Means;
  RealMatrixListType m_Stds;
  RealMatrixListType m_ProdMeans;
  RealMatrixListType m_Mins;
  RealMatrixListType m_Maxs;
  RealMatrixType     m_Area;

private:
  PersistentStatisticsMosaicFilter(const Self&); // purposely not implemented
  void operator=(const Self&);                   // purposely not implemented

}; // end of class


/** \class StreamingStatisticsMosaicFilter
 * \brief This class streams the whole input image through the PersistentStatisticsMosaicFilter.
 *
 * This way, it allows computing the stats of the input images. It calls the
 * Reset() method of the PersistentStatisticsMosaicFilter before streaming the image and the
 * Synthetize() method of the PersistentStatisticsMosaicFilter after having streamed the image
 * to compute the statistics. The accessor on the results are wrapping the accessors of the
 * internal PersistentStatisticsMosaicFilter.
 *
 * \sa PersistentStatisticsMosaicFilter
 * \sa PersistentImageFilter
 * \sa PersistentFilterStreamingDecorator
 * \sa StreamingImageVirtualWriter
 * \ingroup Streamed
 * \ingroup Multithreaded
 * \ingroup Mosaic
 *
 * \ingroup OTBStatistics
 */

template <class TInputImage, class TOutputImage, class TInternalValueType>
class ITK_EXPORT StreamingStatisticsMosaicFilter
    : public PersistentFilterStreamingDecorator<PersistentStatisticsMosaicFilter<TInputImage, TOutputImage, TInternalValueType>>
{
public:
  /** Standard Self typedef */
  typedef StreamingStatisticsMosaicFilter Self;
  typedef PersistentFilterStreamingDecorator<PersistentStatisticsMosaicFilter<TInputImage, TOutputImage, TInternalValueType>> Superclass;
  typedef itk::SmartPointer<Self>       Pointer;
  typedef itk::SmartPointer<const Self> ConstPointer;

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

  /** Creation through object factory macro */
  itkTypeMacro(StreamingStatisticsMosaicFilter, PersistentFilterStreamingDecorator);

  /** Typedefs for statistics */
  typedef typename Superclass::FilterType::RealMatrixType           RealMatrixType;
  typedef typename Superclass::FilterType::RealMatrixObjectType     RealMatrixObjectType;
  typedef typename Superclass::FilterType::RealMatrixListType       RealMatrixListType;
  typedef typename Superclass::FilterType::RealMatrixListObjectType RealMatrixListObjectType;

  /** Input image typedefs.  */
  typedef typename Superclass::FilterType::InputImageType InputImageType;

  using Superclass::PushBackInput;
  void PushBackInput(InputImageType* input)
  {
    this->GetFilter()->PushBackInput(input);
  }

  /** Return the computed Means. */
  RealMatrixListType GetMeans() const
  {
    return this->GetFilter()->GetMeansOutput()->Get();
  }
  RealMatrixListObjectType* GetMeansOutput()
  {
    return this->GetFilter()->GetMeansOutput();
  }
  const RealMatrixListObjectType* GetMeansOutput() const
  {
    return this->GetFilter()->GetMeansOutput();
  }

  /** Return the computed Stds. */
  RealMatrixListType GetStds() const
  {
    return this->GetFilter()->GetStdsOutput()->Get();
  }
  RealMatrixListObjectType* GetStdsOutput()
  {
    return this->GetFilter()->GetStdsOutput();
  }
  const RealMatrixListObjectType* GetStdsOutput() const
  {
    return this->GetFilter()->GetStdsOutput();
  }

  /** Return the computed MeansOfProducts. */
  RealMatrixListType GetMeansOfProducts() const
  {
    return this->GetFilter()->GetMeansOfProductsOutput()->Get();
  }
  RealMatrixListObjectType* GetMeansOfProductsOutput()
  {
    return this->GetFilter()->GetMeansOfProductsOutput();
  }
  const RealMatrixListObjectType* GetMeansOfProductsOutput() const
  {
    return this->GetFilter()->GetMeansOfProductsOutput();
  }

  /** Return the computed Mins. */
  RealMatrixListType GetMins() const
  {
    return this->GetFilter()->GetMinsOutput()->Get();
  }
  RealMatrixListObjectType* GetMinsOutput()
  {
    return this->GetFilter()->GetMinsOutput();
  }
  const RealMatrixListObjectType* GetMinsOutput() const
  {
    return this->GetFilter()->GetMinsOutput();
  }

  /** Return the computed Maxs. */
  RealMatrixListType GetMaxs() const
  {
    return this->GetFilter()->GetMaxsOutput()->Get();
  }
  RealMatrixListObjectType* GetMaxsOutput()
  {
    return this->GetFilter()->GetMaxsOutput();
  }
  const RealMatrixListObjectType* GetMaxsOutput() const
  {
    return this->GetFilter()->GetMaxsOutput();
  }

  /** Return the computed Areas. */
  RealMatrixType GetAreas() const
  {
    return this->GetFilter()->GetAreasOutput()->Get();
  }
  RealMatrixObjectType* GetAreasOutput()
  {
    return this->GetFilter()->GetAreasOutput();
  }
  const RealMatrixObjectType* GetAreasOutput() const
  {
    return this->GetFilter()->GetAreasOutput();
  }

protected:
  /** Constructor */
  StreamingStatisticsMosaicFilter(){};
  /** Destructor */
  ~StreamingStatisticsMosaicFilter() override
  {
  }

private:
  StreamingStatisticsMosaicFilter(const Self&); // purposely not implemented
  void operator=(const Self&);                  // purposely not implemented
};

} // end namespace otb

#ifndef OTB_MANUAL_INSTANTIATION
#include "otbStreamingStatisticsMosaicFilter.hxx"
#endif

#endif