661 lines
21 KiB
C++
661 lines
21 KiB
C++
// ____ ______ __
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// / __ \ / ____// /
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// / /_/ // / / /
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// / ____// /___ / /___ PixInsight Class Library
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// /_/ \____//_____/ PCL 2.4.23
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// ----------------------------------------------------------------------------
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// pcl/Histogram.h - Released 2022-03-12T18:59:29Z
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// ----------------------------------------------------------------------------
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// This file is part of the PixInsight Class Library (PCL).
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// PCL is a multiplatform C++ framework for development of PixInsight modules.
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//
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// Copyright (c) 2003-2022 Pleiades Astrophoto S.L. All Rights Reserved.
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//
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// Redistribution and use in both source and binary forms, with or without
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// modification, is permitted provided that the following conditions are met:
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//
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// 1. All redistributions of source code must retain the above copyright
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// notice, this list of conditions and the following disclaimer.
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//
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// 2. All redistributions in binary form must reproduce the above copyright
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// notice, this list of conditions and the following disclaimer in the
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// documentation and/or other materials provided with the distribution.
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//
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// 3. Neither the names "PixInsight" and "Pleiades Astrophoto", nor the names
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// of their contributors, may be used to endorse or promote products derived
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// from this software without specific prior written permission. For written
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// permission, please contact info@pixinsight.com.
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//
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// 4. All products derived from this software, in any form whatsoever, must
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// reproduce the following acknowledgment in the end-user documentation
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// and/or other materials provided with the product:
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//
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// "This product is based on software from the PixInsight project, developed
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// by Pleiades Astrophoto and its contributors (https://pixinsight.com/)."
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//
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// Alternatively, if that is where third-party acknowledgments normally
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// appear, this acknowledgment must be reproduced in the product itself.
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//
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// THIS SOFTWARE IS PROVIDED BY PLEIADES ASTROPHOTO AND ITS CONTRIBUTORS
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// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
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// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL PLEIADES ASTROPHOTO OR ITS
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// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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// EXEMPLARY OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, BUSINESS
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// INTERRUPTION; PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; AND LOSS OF USE,
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// DATA OR PROFITS) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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// ----------------------------------------------------------------------------
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#ifndef __PCL_Histogram_h
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#define __PCL_Histogram_h
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/// \file pcl/Histogram.h
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#include <pcl/Defs.h>
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#include <pcl/Diagnostics.h>
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#include <pcl/ImageVariant.h>
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#include <pcl/ParallelProcess.h>
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#include <pcl/Vector.h>
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namespace pcl
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{
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// ----------------------------------------------------------------------------
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/*!
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* \class Histogram
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* \brief Discrete image histogram function
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*
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* ### TODO: Write a detailed description for %Histogram.
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*/
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class PCL_CLASS Histogram : public ParallelProcess
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{
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public:
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/*!
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* Represents a histogram bin count, or the value of the discrete histogram
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* function at a specific abscissa or range of abscissae.
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*/
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typedef uint64 count_type;
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/*!
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* A vector of histogram bin counts, which is the type used internally to
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* store the values of the discrete histogram function.
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*/
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typedef UI64Vector histogram_type;
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/*!
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* Constructs an empty %Histogram object with the specified \a resolution.
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*
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* The resolution of a histogram function is the number of discrete
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* intervals (or \e bins) used to analyze image data. The minimum possible
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* resolution is 2. In PCL, the default resolution is 2^16 = 65536 intervals
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* (also known as a <em>16-bit histogram</em>).
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*/
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Histogram( int resolution = 0x10000L )
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: m_resolution( pcl::Max( 2, resolution ) )
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{
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PCL_PRECONDITION( resolution > 1 )
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}
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/*!
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* Constructs a %Histogram object by importing a copy of the specified
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* \a data vector as its internal vector of histogram function values.
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* Automatically sets the histogram resolution equal to the length of the
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* \a data vector, and calculates the peak level of the newly constructed
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* histogram.
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*
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* If the specified \a data vector has less than two components, this
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* constructor will yield an empty histogram with the default 16-bit
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* resolution.
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*/
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Histogram( const histogram_type& data )
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{
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SetHistogramData( data );
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}
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/*!
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* Copy constructor.
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*/
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Histogram( const Histogram& ) = default;
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/*!
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* Move constructor.
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*/
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Histogram( Histogram&& ) = default;
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/*!
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* Destroys a %Histogram object.
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*/
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virtual ~Histogram()
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{
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}
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/*!
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* Copy assignment operator. Returns a reference to this object.
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*/
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Histogram& operator =( const Histogram& ) = default;
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/*!
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* Move assignment operator. Returns a reference to this object.
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*/
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Histogram& operator =( Histogram&& ) = default;
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/*!
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* Assigns another %Histogram object \a x to this object.
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*/
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void Assign( const Histogram& x )
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{
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(void)operator =( x );
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}
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/*!
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* Deallocates the internal vector of histogram values, yielding an empty
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* %Histogram object.
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*/
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void Clear()
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{
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m_histogram.Clear();
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m_peakLevel = 0;
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}
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/*!
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* Returns true iff this %Histogram object is empty. An empty histogram has
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* no computed histogram values.
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*/
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bool IsEmpty() const
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{
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return m_histogram.IsEmpty();
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}
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/*!
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* Returns the current resolution of this %Histogram object.
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*
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* The resolution of a histogram function is the number of discrete
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* intervals (or \e bins) used to analyze image data. The minimum possible
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* resolution is 2. In PCL, the default resolution is 2^16 = 65536 intervals
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* (also known as a <em>16-bit histogram</em>).
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*/
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int Resolution() const
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{
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return m_resolution;
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}
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/*!
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* Returns the highest valid discrete histogram level, or Resolution()-1.
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*/
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int LastLevel() const
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{
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return m_resolution-1;
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}
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/*!
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* Sets the resolution of this %Histogram object.
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*
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* The resolution of a histogram function is the number of discrete
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* intervals (or \e bins) used to analyze image data. The minimum possible
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* resolution is 2. In PCL, the default resolution is 2^16 = 65536 intervals
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* (also known as a <em>16-bit histogram</em>).
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*
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* After calling this member function, the histogram will be empty and the
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* internal vector of histogram function values will be deallocated.
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*/
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void SetResolution( int resolution )
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{
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PCL_PRECONDITION( resolution > 1 )
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Clear();
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m_resolution = pcl::Max( 2, resolution );
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}
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/*!
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* If this histogram object is empty, this member function allocates the
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* internal vector of histogram function values. Newly allocated vectors are
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* not initialized, so the histogram will contain unpredictable values after
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* calling this function.
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*
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* If the histogram is not empty, calling this function has no effect.
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*/
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void Allocate()
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{
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if ( m_histogram.IsEmpty() )
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m_histogram = histogram_type( m_resolution );
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}
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/*!
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* Returns the current peak level of the histogram. If this histogram is
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* empty, the peak level is zero conventionally.
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*
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* The peak level is simply the index (or integer abscissa) of the histogram
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* bin with the largest count, or the position on the X axis of the maximum
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* of the histogram function, in the discrete range [0,LastLevel()].
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*/
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int PeakLevel() const
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{
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return m_histogram.IsEmpty() ? 0 : m_peakLevel;
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}
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/*!
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* Returns the histogram peak level as a floating point number normalized to
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* the [0,1] range. See PeakLevel().
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*/
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double NormalizedPeakLevel() const
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{
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return NormalizedLevel( PeakLevel() );
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}
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/*!
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* Recalculates the histogram peak level from current histogram function
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* values. If the histogram is empty, the peak level is reset to zero
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* conventionally.
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*
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* Returns the newly calculated histogram peak level.
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*/
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int UpdatePeakLevel()
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{
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return m_peakLevel = m_histogram.IsEmpty() ? 0 :
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int( pcl::MaxItem( m_histogram.Begin(), m_histogram.End() ) - m_histogram.Begin() );
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}
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/*!
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* Returns the index of the discrete level in this %Histogram object
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* corresponding to the specified normalized level \a x in the [0,1] range.
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*/
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int HistogramLevel( double x ) const
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{
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PCL_PRECONDITION( x >= 0 && x <= 1 )
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return RoundInt( pcl::Range( x, 0.0, 1.0 )*(m_resolution - 1) );
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}
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/*!
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* Returns the normalized histogram level in the [0,1] range corresponding
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* to the specified discrete level \a i in this %Histogram object.
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*/
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double NormalizedLevel( int i ) const
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{
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PCL_PRECONDITION( i >= 0 && i < m_resolution )
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return double( pcl::Range( i, 0, m_resolution-1 ) )/(m_resolution - 1);
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}
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/*!
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* Converts the specified normalized levels \a a, \a b in the [0,1] range to
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* discrete histogram levels \a i, \a j, respectively.
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*/
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void GetHistogramRange( int& i, int& j, double a, double b ) const
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{
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i = HistogramLevel( a );
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j = HistogramLevel( b );
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if ( j < i )
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pcl::Swap( i, j );
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}
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/*!
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* Converts the specified discrete histogram levels \a i, \a j to normalized
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* levels \a a, \a b, respectively, in the [0,1] range.
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*/
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void GetNormalizedRange( double& a, double& b, int i, int j ) const
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{
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if ( j < i )
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pcl::Swap( i, j );
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a = NormalizedLevel( i );
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b = NormalizedLevel( j );
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}
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/*!
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* Returns the total sum of the counts in all histogram intervals, or the
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* sum of all discrete histogram function values. If this %Histogram object
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* is empty, this function returns zero.
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*/
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count_type Count() const
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{
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return m_histogram.Sum();
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}
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/*!
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* Returns the histogram count, or the value of the histogram function, at
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* the specified discrete level \a i.
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*/
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count_type Count( int i ) const
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{
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PCL_PRECONDITION( i >= 0 && i < m_histogram.Length() )
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if ( i < 0 || i >= m_histogram.Length() )
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return 0;
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return m_histogram[i];
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}
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/*!
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* Subscript operator. Equivalent to Count( int ).
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*/
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count_type operator []( int i ) const
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{
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return Count( i );
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}
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/*!
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* Returns the sum of counts in the specified interval of discrete histogram
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* levels \a i, \a j.
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*/
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count_type Count( int i, int j ) const
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{
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PCL_PRECONDITION( i >= 0 && i < m_histogram.Length() )
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PCL_PRECONDITION( j >= 0 && j < m_histogram.Length() )
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if ( m_histogram.IsEmpty() )
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return 0;
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i = pcl::Range( i, 0, m_histogram.Length()-1 );
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j = pcl::Range( j, 0, m_histogram.Length()-1 );
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if ( j < i )
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pcl::Swap( i, j );
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return pcl::Sum( m_histogram.At( i ), m_histogram.At( j+1 ) );
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}
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/*!
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* Returns the histogram function value for the bin at the current peak
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* level. Typically, the peak count is used to normalize the histogram to
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* a prescribed range. For example, by dividing all histogram function
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* values by the peak count the entire histogram will be normalized to the
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* [0,1] range.
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*/
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count_type PeakCount() const
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{
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return Count( m_peakLevel );
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}
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/*!
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* Returns the peak count, or the maximum histogram function value, within
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* the specified range [i,j] of discrete histogram intervals.
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*/
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count_type PeakCount( int i, int j ) const
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{
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PCL_PRECONDITION( i >= 0 && i < m_histogram.Length() )
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PCL_PRECONDITION( j >= 0 && j < m_histogram.Length() )
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if ( m_histogram.IsEmpty() )
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return 0;
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i = pcl::Range( i, 0, m_histogram.Length()-1 );
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j = pcl::Range( j, 0, m_histogram.Length()-1 );
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if ( j < i )
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pcl::Swap( i, j );
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return *pcl::MaxItem( m_histogram.At( i ), m_histogram.At( j+1 ) );
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}
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/*!
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* Returns the discrete histogram level where the sum of counts for its
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* preceding levels is greater than or equal to the specified amount \a n.
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*
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* This function is useful to compute an automatic histogram shadows
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* clipping point. The returned index is the position of the shadows
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* clipping point that clips (sets to black) the specified amount of image
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* pixel samples
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*/
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int ClipLow( count_type n ) const
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{
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int i = 0;
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for ( count_type s = 0; i < m_histogram.Length()-1 && (s += m_histogram[i]) <= n; ++i ) {}
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return i;
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}
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/*!
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* Returns the normalized histogram level (in the [0,1] range) where the sum
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* of counts for its preceding levels is greater than or equal to the
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* specified amount \a n.
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*/
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double NormalizedClipLow( count_type n ) const
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{
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return NormalizedLevel( ClipLow( n ) );
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}
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/*!
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* Returns the discrete histogram level where the sum of counts for its
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* succeding levels is greater than or equal to the specified amount \a n.
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*
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* This function is useful to compute an automatic histogram highlights
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* clipping point. The returned index is the position of the highlights
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* clipping point that clips (sets to white) the specified amount of image
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* pixel samples
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*/
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int ClipHigh( count_type n ) const
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{
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int i = m_histogram.Length();
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for ( count_type s = 0; --i > 0 && (s += m_histogram[i]) <= n; ) {}
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return i;
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}
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/*!
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* Returns the normalized histogram level (in the [0,1] range) where the sum
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* of counts for its succeding levels is greater than or equal to the
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* specified amount \a n.
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*/
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double NormalizedClipHigh( count_type n ) const
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{
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return NormalizedLevel( ClipHigh( n ) );
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}
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/*!
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* Returns a reference to the immutable internal vector of histogram
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* function values.
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*/
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const histogram_type& HistogramData() const
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{
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return m_histogram;
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}
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/*!
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* Causes this %Histogram object to import a copy of the specified \a data
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* vector as its internal vector of histogram function values. Automatically
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* sets the histogram resolution equal to the length of the \a data vector,
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* and recalculates the peak level of the new histogram.
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*
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* If the specified \a data vector has less than two components, this member
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* function will yield an empty histogram without changing the current
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* histogram resolution.
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*/
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void SetHistogramData( const histogram_type& data )
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{
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if ( data.Length() < 2 )
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Clear();
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else
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{
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m_histogram = data;
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m_resolution = m_histogram.Length();
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UpdatePeakLevel();
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}
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}
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/*!
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* \deprecated This member function has been deprecated. It is kept as part
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* of PCL for compatibility with existing modules; do not use it in newly
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* produced code.
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*/
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void GetData( count_type* where, int fromLevel = 0, int toLevel = -1 ) const
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{
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PCL_PRECONDITION( where != nullptr )
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PCL_PRECONDITION( fromLevel >= 0 )
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if ( where != nullptr )
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if ( !m_histogram.IsEmpty() )
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{
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fromLevel = pcl::Range( fromLevel, 0, m_histogram.Length()-1 );
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toLevel = (toLevel < 0) ? m_histogram.Length()-1 : pcl::Range( toLevel, 0, m_histogram.Length()-1 );
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if ( toLevel < fromLevel )
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pcl::Swap( fromLevel, toLevel );
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::memcpy( where, m_histogram.At( fromLevel ), (1+toLevel-fromLevel)*sizeof( count_type ) );
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}
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}
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/*!
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* Remaps the histogram function to fit the resolution of a target
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* histogram \a h.
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*
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* If the target histogram has the same resolution as this object, this
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* member function is equivalent to a plain assignment. If the resolutions
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* differ, if this histogram is empty then the target histogram is
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* deallocated and cleared, otherwise the target histogram is recomputed as
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* a resampled version of this histogram.
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*
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* This member function is useful to generate reduced versions of a
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* histogram. It can also be used to generate bootstrap samples from an
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* existing histogram function.
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*/
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void Resample( Histogram& h ) const
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{
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if ( h.m_resolution == m_resolution )
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h = *this;
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else
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{
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if ( m_histogram.IsEmpty() )
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h.Clear();
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else
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{
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h.Allocate();
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h.m_histogram = 0;
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double k = double( h.m_histogram.Length() - 1 )/(m_histogram.Length() - 1);
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for ( int i = 0; i < m_histogram.Length(); ++i )
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h.m_histogram[pcl::RoundInt( i*k )] += m_histogram[i];
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h.m_peakLevel = int( pcl::MaxItem( h.m_histogram.Begin(), h.m_histogram.End() ) - h.m_histogram.Begin() );
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}
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}
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}
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/*!
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* Computes the discrete entropy of this histogram.
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*
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* The returned value is normalized to the total weight of the histogram,
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* that is, it is independent on the total number of counts stored in the
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* histogram data vector.
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*/
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double Entropy() const
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{
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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
|