ImageStatistics.h

Go to the documentation of this file.

//     ____   ______ __
//    / __ \ / ____// /
//   / /_/ // /    / /
//  / ____// /___ / /___   PixInsight Class Library
// /_/     \____//_____/   PCL 2.6.11
// ----------------------------------------------------------------------------
// pcl/ImageStatistics.h - Released 2024-05-07T15:27:32Z
// ----------------------------------------------------------------------------
// This file is part of the PixInsight Class Library (PCL).
// PCL is a multiplatform C++ framework for development of PixInsight modules.
//
// Copyright (c) 2003-2024 Pleiades Astrophoto S.L. All Rights Reserved.
//
// Redistribution and use in both source and binary forms, with or without
// modification, is permitted provided that the following conditions are met:
//
// 1. All redistributions of source code must retain the above copyright
//    notice, this list of conditions and the following disclaimer.
//
// 2. All redistributions in binary form must reproduce the above copyright
//    notice, this list of conditions and the following disclaimer in the
//    documentation and/or other materials provided with the distribution.
//
// 3. Neither the names "PixInsight" and "Pleiades Astrophoto", nor the names
//    of their contributors, may be used to endorse or promote products derived
//    from this software without specific prior written permission. For written
//    permission, please contact info@pixinsight.com.
//
// 4. All products derived from this software, in any form whatsoever, must
//    reproduce the following acknowledgment in the end-user documentation
//    and/or other materials provided with the product:
//
//    "This product is based on software from the PixInsight project, developed
//    by Pleiades Astrophoto and its contributors (https://pixinsight.com/)."
//
//    Alternatively, if that is where third-party acknowledgments normally
//    appear, this acknowledgment must be reproduced in the product itself.
//
// THIS SOFTWARE IS PROVIDED BY PLEIADES ASTROPHOTO AND ITS CONTRIBUTORS
// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL PLEIADES ASTROPHOTO OR ITS
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, BUSINESS
// INTERRUPTION; PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; AND LOSS OF USE,
// DATA OR PROFITS) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
// ----------------------------------------------------------------------------
 
#ifndef __PCL_ImageStatistics_h
#define __PCL_ImageStatistics_h
 
 
#include <pcl/Defs.h>
 
#include <pcl/ImageVariant.h>
#include <pcl/ParallelProcess.h>
 
namespace pcl
{
 
// ----------------------------------------------------------------------------
 
class PCL_CLASS ImageStatistics : public ParallelProcess
{
public:
 
   struct PCL_CLASS Data
   {
      size_type count = 0;              
      double    mean = 0;               
      double    sumOfSquares = 0;       
      double    median = 0;             
      double    variance = 0;           
      double    stdDev = 0;             
      double    avgDev = 0;             
      double    MAD = 0;                
      double    bwmv = 0;               
      double    pbmv = 0;               
      double    Sn = 0;                 
      double    Qn = 0;                 
      double    minimum = 0;            
      Point     minPos = Point( 0 );    
      double    maximum = 0;            
      Point     maxPos = Point( 0 );    
      double    low = 0;                
      double    high = 0;               
      bool      rejectLow = false;      
      bool      rejectHigh = false;     
      bool      noExtremes = false;     
      bool      noMean = false;         
      bool      noSumOfSquares = false; 
      bool      noVariance = false;     
      bool      noMedian = false;       
      bool      noAvgDev = false;       
      bool      noMAD = false;          
      bool      noBWMV = false;         
      bool      noPBMV = false;         
      bool      noSn = true;            
      bool      noQn = true;            
 
      Data() = default;
 
      Data( const Data& ) = default;
 
      Data& operator =( const Data& ) = default;
 
      void Assign( const Data& x )
      {
         (void)operator =( x );
      }
 
      void AssignStatisticalData( const Data& x )
      {
         count        = x.count;
         mean         = x.mean;
         sumOfSquares = x.sumOfSquares;
         median       = x.median;
         variance     = x.variance;
         stdDev       = x.stdDev;
         avgDev       = x.avgDev;
         MAD          = x.MAD;
         bwmv         = x.bwmv;
         pbmv         = x.pbmv;
         Sn           = x.Sn;
         Qn           = x.Qn;
         minimum      = x.minimum;
         minPos       = x.minPos;
         maximum      = x.maximum;
         maxPos       = x.maxPos;
      }
   };
 
   // -------------------------------------------------------------------------
 
   ImageStatistics() = default;
 
   ImageStatistics( const ImageStatistics& ) = default;
 
   ~ImageStatistics() override
   {
   }
 
   ImageStatistics& operator =( const ImageStatistics& ) = default;
 
   void Assign( const ImageStatistics& x )
   {
      (void)operator =( x );
   }
 
   const Data& GetData() const
   {
      return m_data;
   }
 
   size_type Count() const
   {
      return m_data.count;
   }
 
   double Mean() const
   {
      return m_data.mean;
   }
 
   double SumOfSquares() const
   {
      return m_data.sumOfSquares;
   }
 
   double Median() const
   {
      return m_data.median;
   }
 
   double Variance() const
   {
      return m_data.variance;
   }
 
   double Var() const
   {
      return Variance();
   }
 
   double StandardDeviation() const
   {
      return m_data.stdDev;
   }
 
   double StdDev() const
   {
      return StandardDeviation();
   }
 
   double AverageDeviation() const
   {
      return m_data.avgDev;
   }
 
   double AvgDev() const
   {
      return AverageDeviation();
   }
 
   double MAD() const
   {
      return m_data.MAD;
   }
 
   double BiweightMidvariance() const
   {
      return m_data.bwmv;
   }
 
   double BWMV() const
   {
      return m_data.bwmv;
   }
 
   double BendMidvariance() const
   {
      return m_data.pbmv;
   }
 
   double PBMV() const
   {
      return m_data.pbmv;
   }
 
   double Sn() const
   {
      return m_data.Sn;
   }
 
   double Qn() const
   {
      return m_data.Qn;
   }
 
   double Minimum() const
   {
      return m_data.minimum;
   }
 
   double Min() const
   {
      return Minimum();
   }
 
   Point MinimumPosition() const
   {
      return m_data.minPos;
   }
 
   Point MinPos() const
   {
      return MinimumPosition();
   }
 
   double Maximum() const
   {
      return m_data.maximum;
   }
 
   double Max() const
   {
      return Maximum();
   }
 
   Point MaximumPosition() const
   {
      return m_data.maxPos;
   }
 
   Point MaxPos() const
   {
      return MaximumPosition();
   }
 
   double RejectionLow() const
   {
      return m_data.low;
   }
 
   double RejectionHigh() const
   {
      return m_data.high;
   }
 
   void SetRejectionLimits( double low, double high )
   {
      m_data.low = Range( low, 0.0, 1.0 );
      m_data.high = Range( high, 0.0, 1.0 );
      if ( m_data.high < m_data.low )
         pcl::Swap( m_data.low, m_data.high );
   }
 
   bool IsLowRejectionEnabled() const
   {
      return m_data.rejectLow;
   }
 
   bool IsHighRejectionEnabled() const
   {
      return m_data.rejectHigh;
   }
 
   void EnableRejection( bool enableLow = true, bool enableHigh = true )
   {
      m_data.rejectLow = enableLow;
      m_data.rejectHigh = enableHigh;
   }
 
   void DisableRejection( bool disableLow = true, bool disableHigh = true )
   {
      EnableRejection( !disableLow, !disableHigh );
   }
 
   bool IsExtremesEnabled() const
   {
      return !m_data.noExtremes;
   }
 
   void EnableExtremes( bool enable = true )
   {
      m_data.noExtremes = !enable;
   }
 
   void DisableExtremes( bool disable = true )
   {
      m_data.noExtremes = disable;
   }
 
   bool IsMeanEnabled() const
   {
      return !m_data.noMean;
   }
 
   void EnableMean( bool enable = true )
   {
      m_data.noMean = !enable;
   }
 
   void DisableMean( bool disable = true )
   {
      m_data.noMean = disable;
   }
 
   bool IsSumOfSquaresEnabled() const
   {
      return !m_data.noSumOfSquares;
   }
 
   void EnableSumOfSquares( bool enable = true )
   {
      m_data.noSumOfSquares = !enable;
   }
 
   void DisableSumOfSquares( bool disable = true )
   {
      m_data.noSumOfSquares = disable;
   }
 
   bool IsVarianceEnabled() const
   {
      return !m_data.noVariance;
   }
 
   void EnableVariance( bool enable = true )
   {
      m_data.noVariance = !enable;
   }
 
   void DisableVariance( bool disable = true )
   {
      m_data.noVariance = disable;
   }
 
   bool IsMedianEnabled() const
   {
      return !m_data.noMedian;
   }
 
   void EnableMedian( bool enable = true )
   {
      m_data.noMedian = !enable;
   }
 
   void DisableMedian( bool disable = true )
   {
      m_data.noMedian = disable;
   }
 
   bool IsAvgDevEnabled() const
   {
      return !m_data.noAvgDev;
   }
 
   void EnableAvgDev( bool enable = true )
   {
      m_data.noAvgDev = !enable;
   }
 
   void DisableAvgDev( bool disable = true )
   {
      m_data.noAvgDev = disable;
   }
 
   bool IsMADEnabled() const
   {
      return !m_data.noMAD;
   }
 
   void EnableMAD( bool enable = true )
   {
      m_data.noMAD = !enable;
   }
 
   void DisableMAD( bool disable = true )
   {
      m_data.noMAD = disable;
   }
 
   bool IsBWMVEnabled() const
   {
      return !m_data.noBWMV;
   }
 
   void EnableBWMV( bool enable = true )
   {
      m_data.noBWMV = !enable;
   }
 
   void DisableBWMV( bool disable = true )
   {
      m_data.noBWMV = disable;
   }
 
   bool IsPBMVEnabled() const
   {
      return !m_data.noPBMV;
   }
 
   void EnablePBMV( bool enable = true )
   {
      m_data.noPBMV = !enable;
   }
 
   void DisablePBMV( bool disable = true )
   {
      m_data.noPBMV = disable;
   }
 
   bool IsSnEnabled() const
   {
      return !m_data.noSn;
   }
 
   void EnableSn( bool enable = true )
   {
      m_data.noSn = !enable;
   }
 
   void DisableSn( bool disable = true )
   {
      m_data.noSn = disable;
   }
 
   bool IsQnEnabled() const
   {
      return !m_data.noQn;
   }
 
   void EnableQn( bool enable = true )
   {
      m_data.noQn = !enable;
   }
 
   void DisableQn( bool disable = true )
   {
      m_data.noQn = disable;
   }
 
   const Image& operator <<( const Image& image );
 
   const DImage& operator <<( const DImage& image );
 
   const UInt8Image& operator <<( const UInt8Image& image );
 
   const UInt16Image& operator <<( const UInt16Image& image );
 
   const UInt32Image& operator <<( const UInt32Image& image );
 
   const ImageVariant& operator <<( const ImageVariant& image )
   {
      if ( image )
         if ( !image.IsComplexSample() )
            if ( image.IsFloatSample() )
               switch ( image.BitsPerSample() )
               {
               case 32: *this << static_cast<const Image&>( *image ); break;
               case 64: *this << static_cast<const DImage&>( *image ); break;
               }
            else
               switch ( image.BitsPerSample() )
               {
               case  8: *this << static_cast<const UInt8Image&>( *image ); break;
               case 16: *this << static_cast<const UInt16Image&>( *image ); break;
               case 32: *this << static_cast<const UInt32Image&>( *image ); break;
               }
      return image;
   }
 
protected:
 
   Data m_data; // statistical data
 
   friend class View;
};
 
// ----------------------------------------------------------------------------
 
} // pcl
 
#endif   // __PCL_ImageStatistics_h
 
// ----------------------------------------------------------------------------
// EOF pcl/ImageStatistics.h - Released 2024-05-07T15:27:32Z