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/* SPDX-License-Identifier: BSD-2-Clause */
/*
* Copyright (C) 2019, Raspberry Pi Ltd
*
* histogram calculations
*/
#include "histogram.h"
#include <cmath>
#include <libcamera/base/log.h>
/**
* \file histogram.h
* \brief Class to represent Histograms and manipulate them
*/
namespace libcamera {
namespace ipa {
/**
* \class Histogram
* \brief The base class for creating histograms
*
* This class stores a cumulative frequency histogram, which is a mapping that
* counts the cumulative number of observations in all of the bins up to the
* specified bin. It can be used to find quantiles and averages between quantiles.
*/
/**
* \fn Histogram::Histogram()
* \brief Construct an empty Histogram
*
* This empty constructor exists largely to allow Histograms to be embedded in
* other classes which may be created before the contents of the Histogram are
* known.
*/
/**
* \brief Create a cumulative histogram
* \param[in] data A pre-sorted histogram to be passed
*/
Histogram::Histogram(Span<const uint32_t> data)
{
cumulative_.reserve(data.size());
cumulative_.push_back(0);
for (const uint32_t &value : data)
cumulative_.push_back(cumulative_.back() + value);
}
/**
* \fn Histogram::bins()
* \brief Retrieve the number of bins currently used by the Histogram
* \return Number of bins
*/
/**
* \fn Histogram::total()
* \brief Retrieve the total number of values in the data set
* \return Number of values
*/
/**
* \brief Cumulative frequency up to a (fractional) point in a bin
* \param[in] bin The bin up to which to cumulate
*
* With F(p) the cumulative frequency of the histogram, the value is 0 at
* the bottom of the histogram, and the maximum is the number of bins.
* The pixels are spread evenly throughout the “bin” in which they lie, so that
* F(p) is a continuous (monotonically increasing) function.
*
* \return The cumulative frequency from 0 up to the specified bin
*/
uint64_t Histogram::cumulativeFrequency(double bin) const
{
if (bin <= 0)
return 0;
else if (bin >= bins())
return total();
int b = static_cast<int32_t>(bin);
return cumulative_[b] +
(bin - b) * (cumulative_[b + 1] - cumulative_[b]);
}
/**
* \brief Return the (fractional) bin of the point through the histogram
* \param[in] q the desired point (0 <= q <= 1)
* \param[in] first low limit (default is 0)
* \param[in] last high limit (default is UINT_MAX)
*
* A quantile gives us the point p = Q(q) in the range such that a proportion
* q of the pixels lie below p. A familiar quantile is Q(0.5) which is the median
* of a distribution.
*
* \return The fractional bin of the point
*/
double Histogram::quantile(double q, uint32_t first, uint32_t last) const
{
if (last == UINT_MAX)
last = cumulative_.size() - 2;
ASSERT(first <= last);
uint64_t item = q * total();
/* Binary search to find the right bin */
while (first < last) {
int middle = (first + last) / 2;
/* Is it between first and middle ? */
if (cumulative_[middle + 1] > item)
last = middle;
else
first = middle + 1;
}
ASSERT(item >= cumulative_[first] && item <= cumulative_[last + 1]);
double frac;
if (cumulative_[first + 1] == cumulative_[first])
frac = 0;
else
frac = (item - cumulative_[first]) / (cumulative_[first + 1] - cumulative_[first]);
return first + frac;
}
/**
* \brief Calculate the mean between two quantiles
* \param[in] lowQuantile low Quantile
* \param[in] highQuantile high Quantile
*
* Quantiles are not ideal for metering as they suffer several limitations.
* Instead, a concept is introduced here: inter-quantile mean.
* It returns the mean of all pixels between lowQuantile and highQuantile.
*
* \return The mean histogram bin value between the two quantiles
*/
double Histogram::interQuantileMean(double lowQuantile, double highQuantile) const
{
ASSERT(highQuantile > lowQuantile);
/* Proportion of pixels which lies below lowQuantile */
double lowPoint = quantile(lowQuantile);
/* Proportion of pixels which lies below highQuantile */
double highPoint = quantile(highQuantile, static_cast<uint32_t>(lowPoint));
double sumBinFreq = 0, cumulFreq = 0;
for (double p_next = floor(lowPoint) + 1.0;
p_next <= ceil(highPoint);
lowPoint = p_next, p_next += 1.0) {
int bin = floor(lowPoint);
double freq = (cumulative_[bin + 1] - cumulative_[bin])
* (std::min(p_next, highPoint) - lowPoint);
/* Accumulate weighted bin */
sumBinFreq += bin * freq;
/* Accumulate weights */
cumulFreq += freq;
}
/* add 0.5 to give an average for bin mid-points */
return sumBinFreq / cumulFreq + 0.5;
}
} /* namespace ipa */
} /* namespace libcamera */
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