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3rdparty/include/pcl/Histogram.h
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// ____ ______ __
// / __ \ / ____// /
// / /_/ // / / /
// / ____// /___ / /___ PixInsight Class Library
// /_/ \____//_____/ PCL 2.4.23
// ----------------------------------------------------------------------------
// pcl/Histogram.h - Released 2022-03-12T18:59:29Z
// ----------------------------------------------------------------------------
// This file is part of the PixInsight Class Library (PCL).
// PCL is a multiplatform C++ framework for development of PixInsight modules.
//
// Copyright (c) 2003-2022 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_Histogram_h
#define __PCL_Histogram_h
/// \file pcl/Histogram.h
#include <pcl/Defs.h>
#include <pcl/Diagnostics.h>
#include <pcl/ImageVariant.h>
#include <pcl/ParallelProcess.h>
#include <pcl/Vector.h>
namespace pcl
{
// ----------------------------------------------------------------------------
/*!
* \class Histogram
* \brief Discrete image histogram function
*
* ### TODO: Write a detailed description for %Histogram.
*/
class PCL_CLASS Histogram : public ParallelProcess
{
public:
/*!
* Represents a histogram bin count, or the value of the discrete histogram
* function at a specific abscissa or range of abscissae.
*/
typedef uint64 count_type;
/*!
* A vector of histogram bin counts, which is the type used internally to
* store the values of the discrete histogram function.
*/
typedef UI64Vector histogram_type;
/*!
* Constructs an empty %Histogram object with the specified \a resolution.
*
* The resolution of a histogram function is the number of discrete
* intervals (or \e bins) used to analyze image data. The minimum possible
* resolution is 2. In PCL, the default resolution is 2^16 = 65536 intervals
* (also known as a <em>16-bit histogram</em>).
*/
Histogram( int resolution = 0x10000L )
: m_resolution( pcl::Max( 2, resolution ) )
{
PCL_PRECONDITION( resolution > 1 )
}
/*!
* Constructs a %Histogram object by importing a copy of the specified
* \a data vector as its internal vector of histogram function values.
* Automatically sets the histogram resolution equal to the length of the
* \a data vector, and calculates the peak level of the newly constructed
* histogram.
*
* If the specified \a data vector has less than two components, this
* constructor will yield an empty histogram with the default 16-bit
* resolution.
*/
Histogram( const histogram_type& data )
{
SetHistogramData( data );
}
/*!
* Copy constructor.
*/
Histogram( const Histogram& ) = default;
/*!
* Move constructor.
*/
Histogram( Histogram&& ) = default;
/*!
* Destroys a %Histogram object.
*/
virtual ~Histogram()
{
}
/*!
* Copy assignment operator. Returns a reference to this object.
*/
Histogram& operator =( const Histogram& ) = default;
/*!
* Move assignment operator. Returns a reference to this object.
*/
Histogram& operator =( Histogram&& ) = default;
/*!
* Assigns another %Histogram object \a x to this object.
*/
void Assign( const Histogram& x )
{
(void)operator =( x );
}
/*!
* Deallocates the internal vector of histogram values, yielding an empty
* %Histogram object.
*/
void Clear()
{
m_histogram.Clear();
m_peakLevel = 0;
}
/*!
* Returns true iff this %Histogram object is empty. An empty histogram has
* no computed histogram values.
*/
bool IsEmpty() const
{
return m_histogram.IsEmpty();
}
/*!
* Returns the current resolution of this %Histogram object.
*
* The resolution of a histogram function is the number of discrete
* intervals (or \e bins) used to analyze image data. The minimum possible
* resolution is 2. In PCL, the default resolution is 2^16 = 65536 intervals
* (also known as a <em>16-bit histogram</em>).
*/
int Resolution() const
{
return m_resolution;
}
/*!
* Returns the highest valid discrete histogram level, or Resolution()-1.
*/
int LastLevel() const
{
return m_resolution-1;
}
/*!
* Sets the resolution of this %Histogram object.
*
* The resolution of a histogram function is the number of discrete
* intervals (or \e bins) used to analyze image data. The minimum possible
* resolution is 2. In PCL, the default resolution is 2^16 = 65536 intervals
* (also known as a <em>16-bit histogram</em>).
*
* After calling this member function, the histogram will be empty and the
* internal vector of histogram function values will be deallocated.
*/
void SetResolution( int resolution )
{
PCL_PRECONDITION( resolution > 1 )
Clear();
m_resolution = pcl::Max( 2, resolution );
}
/*!
* If this histogram object is empty, this member function allocates the
* internal vector of histogram function values. Newly allocated vectors are
* not initialized, so the histogram will contain unpredictable values after
* calling this function.
*
* If the histogram is not empty, calling this function has no effect.
*/
void Allocate()
{
if ( m_histogram.IsEmpty() )
m_histogram = histogram_type( m_resolution );
}
/*!
* Returns the current peak level of the histogram. If this histogram is
* empty, the peak level is zero conventionally.
*
* The peak level is simply the index (or integer abscissa) of the histogram
* bin with the largest count, or the position on the X axis of the maximum
* of the histogram function, in the discrete range [0,LastLevel()].
*/
int PeakLevel() const
{
return m_histogram.IsEmpty() ? 0 : m_peakLevel;
}
/*!
* Returns the histogram peak level as a floating point number normalized to
* the [0,1] range. See PeakLevel().
*/
double NormalizedPeakLevel() const
{
return NormalizedLevel( PeakLevel() );
}
/*!
* Recalculates the histogram peak level from current histogram function
* values. If the histogram is empty, the peak level is reset to zero
* conventionally.
*
* Returns the newly calculated histogram peak level.
*/
int UpdatePeakLevel()
{
return m_peakLevel = m_histogram.IsEmpty() ? 0 :
int( pcl::MaxItem( m_histogram.Begin(), m_histogram.End() ) - m_histogram.Begin() );
}
/*!
* Returns the index of the discrete level in this %Histogram object
* corresponding to the specified normalized level \a x in the [0,1] range.
*/
int HistogramLevel( double x ) const
{
PCL_PRECONDITION( x >= 0 && x <= 1 )
return RoundInt( pcl::Range( x, 0.0, 1.0 )*(m_resolution - 1) );
}
/*!
* Returns the normalized histogram level in the [0,1] range corresponding
* to the specified discrete level \a i in this %Histogram object.
*/
double NormalizedLevel( int i ) const
{
PCL_PRECONDITION( i >= 0 && i < m_resolution )
return double( pcl::Range( i, 0, m_resolution-1 ) )/(m_resolution - 1);
}
/*!
* Converts the specified normalized levels \a a, \a b in the [0,1] range to
* discrete histogram levels \a i, \a j, respectively.
*/
void GetHistogramRange( int& i, int& j, double a, double b ) const
{
i = HistogramLevel( a );
j = HistogramLevel( b );
if ( j < i )
pcl::Swap( i, j );
}
/*!
* Converts the specified discrete histogram levels \a i, \a j to normalized
* levels \a a, \a b, respectively, in the [0,1] range.
*/
void GetNormalizedRange( double& a, double& b, int i, int j ) const
{
if ( j < i )
pcl::Swap( i, j );
a = NormalizedLevel( i );
b = NormalizedLevel( j );
}
/*!
* Returns the total sum of the counts in all histogram intervals, or the
* sum of all discrete histogram function values. If this %Histogram object
* is empty, this function returns zero.
*/
count_type Count() const
{
return m_histogram.Sum();
}
/*!
* Returns the histogram count, or the value of the histogram function, at
* the specified discrete level \a i.
*/
count_type Count( int i ) const
{
PCL_PRECONDITION( i >= 0 && i < m_histogram.Length() )
if ( i < 0 || i >= m_histogram.Length() )
return 0;
return m_histogram[i];
}
/*!
* Subscript operator. Equivalent to Count( int ).
*/
count_type operator []( int i ) const
{
return Count( i );
}
/*!
* Returns the sum of counts in the specified interval of discrete histogram
* levels \a i, \a j.
*/
count_type Count( int i, int j ) const
{
PCL_PRECONDITION( i >= 0 && i < m_histogram.Length() )
PCL_PRECONDITION( j >= 0 && j < m_histogram.Length() )
if ( m_histogram.IsEmpty() )
return 0;
i = pcl::Range( i, 0, m_histogram.Length()-1 );
j = pcl::Range( j, 0, m_histogram.Length()-1 );
if ( j < i )
pcl::Swap( i, j );
return pcl::Sum( m_histogram.At( i ), m_histogram.At( j+1 ) );
}
/*!
* Returns the histogram function value for the bin at the current peak
* level. Typically, the peak count is used to normalize the histogram to
* a prescribed range. For example, by dividing all histogram function
* values by the peak count the entire histogram will be normalized to the
* [0,1] range.
*/
count_type PeakCount() const
{
return Count( m_peakLevel );
}
/*!
* Returns the peak count, or the maximum histogram function value, within
* the specified range [i,j] of discrete histogram intervals.
*/
count_type PeakCount( int i, int j ) const
{
PCL_PRECONDITION( i >= 0 && i < m_histogram.Length() )
PCL_PRECONDITION( j >= 0 && j < m_histogram.Length() )
if ( m_histogram.IsEmpty() )
return 0;
i = pcl::Range( i, 0, m_histogram.Length()-1 );
j = pcl::Range( j, 0, m_histogram.Length()-1 );
if ( j < i )
pcl::Swap( i, j );
return *pcl::MaxItem( m_histogram.At( i ), m_histogram.At( j+1 ) );
}
/*!
* Returns the discrete histogram level where the sum of counts for its
* preceding levels is greater than or equal to the specified amount \a n.
*
* This function is useful to compute an automatic histogram shadows
* clipping point. The returned index is the position of the shadows
* clipping point that clips (sets to black) the specified amount of image
* pixel samples
*/
int ClipLow( count_type n ) const
{
int i = 0;
for ( count_type s = 0; i < m_histogram.Length()-1 && (s += m_histogram[i]) <= n; ++i ) {}
return i;
}
/*!
* Returns the normalized histogram level (in the [0,1] range) where the sum
* of counts for its preceding levels is greater than or equal to the
* specified amount \a n.
*/
double NormalizedClipLow( count_type n ) const
{
return NormalizedLevel( ClipLow( n ) );
}
/*!
* Returns the discrete histogram level where the sum of counts for its
* succeding levels is greater than or equal to the specified amount \a n.
*
* This function is useful to compute an automatic histogram highlights
* clipping point. The returned index is the position of the highlights
* clipping point that clips (sets to white) the specified amount of image
* pixel samples
*/
int ClipHigh( count_type n ) const
{
int i = m_histogram.Length();
for ( count_type s = 0; --i > 0 && (s += m_histogram[i]) <= n; ) {}
return i;
}
/*!
* Returns the normalized histogram level (in the [0,1] range) where the sum
* of counts for its succeding levels is greater than or equal to the
* specified amount \a n.
*/
double NormalizedClipHigh( count_type n ) const
{
return NormalizedLevel( ClipHigh( n ) );
}
/*!
* Returns a reference to the immutable internal vector of histogram
* function values.
*/
const histogram_type& HistogramData() const
{
return m_histogram;
}
/*!
* Causes this %Histogram object to import a copy of the specified \a data
* vector as its internal vector of histogram function values. Automatically
* sets the histogram resolution equal to the length of the \a data vector,
* and recalculates the peak level of the new histogram.
*
* If the specified \a data vector has less than two components, this member
* function will yield an empty histogram without changing the current
* histogram resolution.
*/
void SetHistogramData( const histogram_type& data )
{
if ( data.Length() < 2 )
Clear();
else
{
m_histogram = data;
m_resolution = m_histogram.Length();
UpdatePeakLevel();
}
}
/*!
* \deprecated This member function has been deprecated. It is kept as part
* of PCL for compatibility with existing modules; do not use it in newly
* produced code.
*/
void GetData( count_type* where, int fromLevel = 0, int toLevel = -1 ) const
{
PCL_PRECONDITION( where != nullptr )
PCL_PRECONDITION( fromLevel >= 0 )
if ( where != nullptr )
if ( !m_histogram.IsEmpty() )
{
fromLevel = pcl::Range( fromLevel, 0, m_histogram.Length()-1 );
toLevel = (toLevel < 0) ? m_histogram.Length()-1 : pcl::Range( toLevel, 0, m_histogram.Length()-1 );
if ( toLevel < fromLevel )
pcl::Swap( fromLevel, toLevel );
::memcpy( where, m_histogram.At( fromLevel ), (1+toLevel-fromLevel)*sizeof( count_type ) );
}
}
/*!
* Remaps the histogram function to fit the resolution of a target
* histogram \a h.
*
* If the target histogram has the same resolution as this object, this
* member function is equivalent to a plain assignment. If the resolutions
* differ, if this histogram is empty then the target histogram is
* deallocated and cleared, otherwise the target histogram is recomputed as
* a resampled version of this histogram.
*
* This member function is useful to generate reduced versions of a
* histogram. It can also be used to generate bootstrap samples from an
* existing histogram function.
*/
void Resample( Histogram& h ) const
{
if ( h.m_resolution == m_resolution )
h = *this;
else
{
if ( m_histogram.IsEmpty() )
h.Clear();
else
{
h.Allocate();
h.m_histogram = 0;
double k = double( h.m_histogram.Length() - 1 )/(m_histogram.Length() - 1);
for ( int i = 0; i < m_histogram.Length(); ++i )
h.m_histogram[pcl::RoundInt( i*k )] += m_histogram[i];
h.m_peakLevel = int( pcl::MaxItem( h.m_histogram.Begin(), h.m_histogram.End() ) - h.m_histogram.Begin() );
}
}
}
/*!
* Computes the discrete entropy of this histogram.
*
* The returned value is normalized to the total weight of the histogram,
* that is, it is independent on the total number of counts stored in the
* histogram data vector.
*/
double Entropy() const
{
double H = 0;
count_type n = Count();
if ( n > 0 )
for ( int i = 0; i < m_histogram.Length(); ++i )
if ( m_histogram[i] > 0 )
{
double f = double( m_histogram[i] )/n;
H -= f*Log( f );
}
return H;
}
/*!
* Computes the histogram function of a 32-bit floating point real image.
*/
const Image& operator <<( const Image& );
/*!
* Computes the histogram function of a 64-bit floating point real image.
*/
const DImage& operator <<( const DImage& );
/*!
* Computes the histogram function of an 8-bit unsigned integer image.
*/
const UInt8Image& operator <<( const UInt8Image& );
/*!
* Computes the histogram function of a 16-bit unsigned integer image.
*/
const UInt16Image& operator <<( const UInt16Image& );
/*!
* Computes the histogram function of a 32-bit unsigned integer image.
*/
const UInt32Image& operator <<( const UInt32Image& );
/*!
* Computes the histogram function of the image transported by an
* ImageVariant object.
*/
const ImageVariant& operator <<( const ImageVariant& );
/*!
* Returns the current rectangular selection in this %Histogram object.
*
* By default, the rectangular selection is an empy rectangle, meaning that
* the rectangular selection in the target image will be used.
*/
const Rect& SelectedRectangle() const
{
return m_rect;
}
/*!
* Sets a new rectangular selection for this %Histogram object.
*
* When a non-empty rectangular selection is specified, it is used as the
* region of interest (ROI) for calculation of histograms. If an empty or
* invalid rectangle is specified, the current selection in the target image
* will be used.
*/
void SelectRectangle( const Rect& r )
{
m_rect = r;
}
/*!
* Clears the rectangular selection in this %Histogram object.
*
* After calling this function, histograms will be calculated for the
* current rectangular selection of the target image.
*/
void ClearRectangle()
{
m_rect = Rect( 0 );
}
/*!
* Returns the current channel index selected in this %Histogram object.
*
* By default, the selected channel index is -1, meaning that the channel
* selected in the target image will be used.
*/
int SelectedChannel() const
{
return m_channel;
}
/*!
* Selects a channel index for this %Histogram object.
*
* When a positive (>= 0) channel index is specified, it is used for
* calculation of histograms. If a negative channel index is specified, the
* current selected channel in the target image will be used.
*/
void SelectChannel( int channel )
{
m_channel = pcl::Max( -1, channel );
}
/*!
* Clears the channel index selection in this %Histogram object.
*
* After calling this function, histograms will be calculated for the
* current selected channel of the target image.
*/
void ClearSelectedChannel()
{
m_channel = -1;
}
protected:
histogram_type m_histogram; // Discrete histogram levels
int m_resolution = 0x10000L; // Number of histogram levels
int m_peakLevel = 0; // Maximum level (index of maximum count)
Rect m_rect = 0; // ROI, Rect( 0 ) to use target image's selection
int m_channel = -1; // < 0 to use target image's selection
friend class View;
friend class HistogramTransformation;
};
// ----------------------------------------------------------------------------
} // pcl
#endif // __PCL_Histogram_h
// ----------------------------------------------------------------------------
// EOF pcl/Histogram.h - Released 2022-03-12T18:59:29Z