From 80ac19a50795dea80c4bad33588e1fc6df1ef3e6 Mon Sep 17 00:00:00 2001 From: Stefan Klug Date: Tue, 1 Apr 2025 14:36:13 +0200 Subject: libipa: histogram: Fix interQuantileMean() for small ranges The interQuantileMean() is supposed to return a weighted mean value between two quantiles. This works for fine histograms, but fails for coarse histograms and small quantile ranges because the weight is always taken from the lower border of the bin. Fix that by rewriting the algorithm to calculate a lower and upper bound for every (partial) bin that goes into the mean calculation and weight the bins by the middle of these bounds. Signed-off-by: Stefan Klug Acked-by: Kieran Bingham Reviewed-by: Laurent Pinchart --- src/ipa/libipa/histogram.cpp | 39 +++++++++++++++++++++++++-------------- test/ipa/libipa/meson.build | 2 +- 2 files changed, 26 insertions(+), 15 deletions(-) diff --git a/src/ipa/libipa/histogram.cpp b/src/ipa/libipa/histogram.cpp index ea042f0a..bcf26390 100644 --- a/src/ipa/libipa/histogram.cpp +++ b/src/ipa/libipa/histogram.cpp @@ -149,26 +149,37 @@ double Histogram::quantile(double q, uint32_t first, uint32_t last) const 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(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); + + /* Proportion of pixels which lies below lowQuantile and highQuantile. */ + const double lowPoint = quantile(lowQuantile); + const double highPoint = quantile(highQuantile, static_cast(lowPoint)); + + double sumBinFreq = 0; + double cumulFreq = 0; + + /* + * Calculate the mean pixel value between the low and high points by + * summing all the pixels between the two points, and dividing the sum + * by the number of pixels. Given the discrete nature of the histogram + * data, the sum of the pixels is approximated by accumulating the + * product of the bin values (calculated as the mid point of the bin) by + * the number of pixels they contain, for each bin in the internal. + */ + for (unsigned bin = std::floor(lowPoint); bin < std::ceil(highPoint); bin++) { + const double lowBound = std::max(bin, lowPoint); + const double highBound = std::min(bin + 1, highPoint); + double freq = (cumulative_[bin + 1] - cumulative_[bin]) - * (std::min(p_next, highPoint) - lowPoint); + * (highBound - lowBound); /* Accumulate weighted bin */ - sumBinFreq += bin * freq; + sumBinFreq += (highBound + lowBound) / 2 * freq; + /* Accumulate weights */ cumulFreq += freq; } - /* add 0.5 to give an average for bin mid-points */ - return sumBinFreq / cumulFreq + 0.5; + + return sumBinFreq / cumulFreq; } } /* namespace ipa */ diff --git a/test/ipa/libipa/meson.build b/test/ipa/libipa/meson.build index 83c84bd8..8c63ebd8 100644 --- a/test/ipa/libipa/meson.build +++ b/test/ipa/libipa/meson.build @@ -2,7 +2,7 @@ libipa_test = [ {'name': 'fixedpoint', 'sources': ['fixedpoint.cpp']}, - {'name': 'histogram', 'sources': ['histogram.cpp'], 'should_fail': true}, + {'name': 'histogram', 'sources': ['histogram.cpp']}, {'name': 'interpolator', 'sources': ['interpolator.cpp']}, ] -- cgit v1.2.1