--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/mupdf-source/thirdparty/zxing-cpp/core/src/HybridBinarizer.cpp	Mon Sep 15 11:43:07 2025 +0200
@@ -0,0 +1,313 @@
+/*
+* Copyright 2016 Nu-book Inc.
+* Copyright 2016 ZXing authors
+*/
+// SPDX-License-Identifier: Apache-2.0
+
+#include "HybridBinarizer.h"
+
+#include "BitMatrix.h"
+#include "Matrix.h"
+
+#include <algorithm>
+#include <cstdint>
+#include <fstream>
+#include <memory>
+
+#define USE_NEW_ALGORITHM
+
+namespace ZXing {
+
+// This class uses 5x5 blocks to compute local luminance, where each block is 8x8 pixels.
+// So this is the smallest dimension in each axis we can accept.
+static constexpr int BLOCK_SIZE = 8;
+static constexpr int WINDOW_SIZE = BLOCK_SIZE * (1 + 2 * 2);
+static constexpr int MIN_DYNAMIC_RANGE = 24;
+
+HybridBinarizer::HybridBinarizer(const ImageView& iv) : GlobalHistogramBinarizer(iv) {}
+
+HybridBinarizer::~HybridBinarizer() = default;
+
+bool HybridBinarizer::getPatternRow(int row, int rotation, PatternRow& res) const
+{
+#if 1
+	// This is the original "hybrid" behavior: use GlobalHistogram for the 1D case
+	return GlobalHistogramBinarizer::getPatternRow(row, rotation, res);
+#else
+	// This is an alternative that can be faster in general and perform better in unevenly lit sitations like
+	// https://github.com/zxing-cpp/zxing-cpp/blob/master/test/samples/ean13-2/21.png. That said, it fairs
+	// worse in borderline low resolution situations. With the current black box sample set we'd loose 94
+	// test cases while gaining 53 others.
+	auto bits = getBitMatrix();
+	if (bits)
+		GetPatternRow(*bits, row, res, rotation % 180 != 0);
+	return bits != nullptr;
+#endif
+}
+
+using T_t = uint8_t;
+
+/**
+* Applies a single threshold to a block of pixels.
+*/
+static void ThresholdBlock(const uint8_t* __restrict luminances, int xoffset, int yoffset, T_t threshold, int rowStride,
+						   BitMatrix& matrix)
+{
+	for (int y = yoffset; y < yoffset + BLOCK_SIZE; ++y) {
+		auto* src = luminances + y * rowStride + xoffset;
+		auto* const dstBegin = matrix.row(y).begin() + xoffset;
+		// TODO: fix pixelStride > 1 case
+		for (auto* dst = dstBegin; dst < dstBegin + BLOCK_SIZE; ++dst, ++src)
+			*dst = (*src <= threshold) * BitMatrix::SET_V;
+	}
+}
+
+#ifndef USE_NEW_ALGORITHM
+
+/**
+* Calculates a single black point for each block of pixels and saves it away.
+* See the following thread for a discussion of this algorithm:
+*  http://groups.google.com/group/zxing/browse_thread/thread/d06efa2c35a7ddc0
+*/
+static Matrix<T_t> CalculateBlackPoints(const uint8_t* __restrict luminances, int subWidth, int subHeight, int width, int height,
+										int rowStride)
+{
+	Matrix<T_t> blackPoints(subWidth, subHeight);
+
+	for (int y = 0; y < subHeight; y++) {
+		int yoffset = std::min(y * BLOCK_SIZE, height - BLOCK_SIZE);
+		for (int x = 0; x < subWidth; x++) {
+			int xoffset = std::min(x * BLOCK_SIZE, width - BLOCK_SIZE);
+			int sum = 0;
+			uint8_t min = luminances[yoffset * rowStride + xoffset];
+			uint8_t max = min;
+			for (int yy = 0, offset = yoffset * rowStride + xoffset; yy < BLOCK_SIZE; yy++, offset += rowStride) {
+				for (int xx = 0; xx < BLOCK_SIZE; xx++) {
+					auto pixel = luminances[offset + xx];
+					sum += pixel;
+					if (pixel < min)
+						min = pixel;
+					if (pixel > max)
+						max = pixel;
+				}
+				// short-circuit min/max tests once dynamic range is met
+				if (max - min > MIN_DYNAMIC_RANGE) {
+					// finish the rest of the rows quickly
+					for (yy++, offset += rowStride; yy < BLOCK_SIZE; yy++, offset += rowStride) {
+						for (int xx = 0; xx < BLOCK_SIZE; xx++) {
+							sum += luminances[offset + xx];
+						}
+					}
+				}
+			}
+
+			// The default estimate is the average of the values in the block.
+			int average = sum / (BLOCK_SIZE * BLOCK_SIZE);
+			if (max - min <= MIN_DYNAMIC_RANGE) {
+				// If variation within the block is low, assume this is a block with only light or only
+				// dark pixels. In that case we do not want to use the average, as it would divide this
+				// low contrast area into black and white pixels, essentially creating data out of noise.
+				//
+				// The default assumption is that the block is light/background. Since no estimate for
+				// the level of dark pixels exists locally, use half the min for the block.
+				average = min / 2;
+
+				if (y > 0 && x > 0) {
+					// Correct the "white background" assumption for blocks that have neighbors by comparing
+					// the pixels in this block to the previously calculated black points. This is based on
+					// the fact that dark barcode symbology is always surrounded by some amount of light
+					// background for which reasonable black point estimates were made. The bp estimated at
+					// the boundaries is used for the interior.
+
+					// The (min < bp) is arbitrary but works better than other heuristics that were tried.
+					int averageNeighborBlackPoint =
+						(blackPoints(x, y - 1) + (2 * blackPoints(x - 1, y)) + blackPoints(x - 1, y - 1)) / 4;
+					if (min < averageNeighborBlackPoint) {
+						average = averageNeighborBlackPoint;
+					}
+				}
+			}
+			blackPoints(x, y) = average;
+		}
+	}
+	return blackPoints;
+}
+
+/**
+* For each block in the image, calculate the average black point using a 5x5 grid
+* of the blocks around it. Also handles the corner cases (fractional blocks are computed based
+* on the last pixels in the row/column which are also used in the previous block).
+*/
+static std::shared_ptr<BitMatrix> CalculateMatrix(const uint8_t* __restrict luminances, int subWidth, int subHeight, int width,
+												  int height, int rowStride, const Matrix<T_t>& blackPoints)
+{
+	auto matrix = std::make_shared<BitMatrix>(width, height);
+
+#ifdef PRINT_DEBUG
+	Matrix<uint8_t> out(width, height);
+	Matrix<uint8_t> out2(width, height);
+#endif
+
+	for (int y = 0; y < subHeight; y++) {
+		int yoffset = std::min(y * BLOCK_SIZE, height - BLOCK_SIZE);
+		for (int x = 0; x < subWidth; x++) {
+			int xoffset = std::min(x * BLOCK_SIZE, width - BLOCK_SIZE);
+			int left = std::clamp(x, 2, subWidth - 3);
+			int top = std::clamp(y, 2, subHeight - 3);
+			int sum = 0;
+			for (int dy = -2; dy <= 2; ++dy) {
+				for (int dx = -2; dx <= 2; ++dx) {
+					sum += blackPoints(left + dx, top + dy);
+				}
+			}
+			int average = sum / 25;
+			ThresholdBlock(luminances, xoffset, yoffset, average, rowStride, *matrix);
+
+#ifdef PRINT_DEBUG
+			for (int yy = 0; yy < 8; ++yy)
+				for (int xx = 0; xx < 8; ++xx) {
+					out.set(xoffset + xx, yoffset + yy, blackPoints(x, y));
+					out2.set(xoffset + xx, yoffset + yy, average);
+				}
+#endif
+		}
+	}
+
+#ifdef PRINT_DEBUG
+	std::ofstream file("thresholds.pnm");
+	file << "P5\n" << out.width() << ' ' << out.height() << "\n255\n";
+	file.write(reinterpret_cast<const char*>(out.data()), out.size());
+	std::ofstream file2("thresholds_avg.pnm");
+	file2 << "P5\n" << out.width() << ' ' << out.height() << "\n255\n";
+	file2.write(reinterpret_cast<const char*>(out2.data()), out2.size());
+#endif
+
+	return matrix;
+}
+
+#else
+
+// Subdivide the image in blocks of BLOCK_SIZE and calculate one treshold value per block as
+// (max - min > MIN_DYNAMIC_RANGE) ? (max + min) / 2 : 0
+static Matrix<T_t> BlockThresholds(const ImageView iv)
+{
+	int subWidth = (iv.width() + BLOCK_SIZE - 1) / BLOCK_SIZE; // ceil(width/BS)
+	int subHeight = (iv.height() + BLOCK_SIZE - 1) / BLOCK_SIZE; // ceil(height/BS)
+
+	Matrix<T_t> thresholds(subWidth, subHeight);
+
+	for (int y = 0; y < subHeight; y++) {
+		int y0 = std::min(y * BLOCK_SIZE, iv.height() - BLOCK_SIZE);
+		for (int x = 0; x < subWidth; x++) {
+			int x0 = std::min(x * BLOCK_SIZE, iv.width() - BLOCK_SIZE);
+			uint8_t min = 255;
+			uint8_t max = 0;
+			for (int yy = 0; yy < BLOCK_SIZE; yy++) {
+				auto line = iv.data(x0, y0 + yy);
+				for (int xx = 0; xx < BLOCK_SIZE; xx++)
+					UpdateMinMax(min, max, line[xx]);
+			}
+
+			thresholds(x, y) = (max - min > MIN_DYNAMIC_RANGE) ? (int(max) + min) / 2 : 0;
+		}
+	}
+
+	return thresholds;
+}
+
+// Apply gaussian-like smoothing filter over all non-zero thresholds and fill any remainig gaps with nearest neighbor
+static Matrix<T_t> SmoothThresholds(Matrix<T_t>&& in)
+{
+	Matrix<T_t> out(in.width(), in.height());
+
+	constexpr int R = WINDOW_SIZE / BLOCK_SIZE / 2;
+	for (int y = 0; y < in.height(); y++) {
+		for (int x = 0; x < in.width(); x++) {
+			int left = std::clamp(x, R, in.width() - R - 1);
+			int top = std::clamp(y, R, in.height() - R - 1);
+
+			int sum = in(x, y) * 2;
+			int n = (sum > 0) * 2;
+			auto add = [&](int x, int y) {
+				int t = in(x, y);
+				sum += t;
+				n += t > 0;
+			};
+
+			for (int dy = -R; dy <= R; ++dy)
+				for (int dx = -R; dx <= R; ++dx)
+					add(left + dx, top + dy);
+
+			out(x, y) = n > 0 ? sum / n : 0;
+		}
+	}
+
+	// flood fill any remaing gaps of (very large) no-contrast regions
+	auto last = out.begin() - 1;
+	for (auto* i = out.begin(); i != out.end(); ++i) {
+		if (*i) {
+			if (last != i - 1)
+				std::fill(last + 1, i, *i);
+			last = i;
+		}
+	}
+	std::fill(last + 1, out.end(), *(std::max(last, out.begin())));
+
+	return out;
+}
+
+static std::shared_ptr<BitMatrix> ThresholdImage(const ImageView iv, const Matrix<T_t>& thresholds)
+{
+	auto matrix = std::make_shared<BitMatrix>(iv.width(), iv.height());
+
+#ifdef PRINT_DEBUG
+	Matrix<uint8_t> out(iv.width(), iv.height());
+#endif
+
+	for (int y = 0; y < thresholds.height(); y++) {
+		int yoffset = std::min(y * BLOCK_SIZE, iv.height() - BLOCK_SIZE);
+		for (int x = 0; x < thresholds.width(); x++) {
+			int xoffset = std::min(x * BLOCK_SIZE, iv.width() - BLOCK_SIZE);
+			ThresholdBlock(iv.data(), xoffset, yoffset, thresholds(x, y), iv.rowStride(), *matrix);
+
+#ifdef PRINT_DEBUG
+			for (int yy = 0; yy < 8; ++yy)
+				for (int xx = 0; xx < 8; ++xx)
+					out.set(xoffset + xx, yoffset + yy, thresholds(x, y));
+#endif
+		}
+	}
+
+#ifdef PRINT_DEBUG
+	std::ofstream file("thresholds_new.pnm");
+	file << "P5\n" << out.width() << ' ' << out.height() << "\n255\n";
+	file.write(reinterpret_cast<const char*>(out.data()), out.size());
+#endif
+
+	return matrix;
+}
+
+#endif
+
+std::shared_ptr<const BitMatrix> HybridBinarizer::getBlackMatrix() const
+{
+	if (width() >= WINDOW_SIZE && height() >= WINDOW_SIZE) {
+#ifdef USE_NEW_ALGORITHM
+		auto thrs = SmoothThresholds(BlockThresholds(_buffer));
+		return ThresholdImage(_buffer, thrs);
+#else
+		const uint8_t* luminances = _buffer.data();
+		int subWidth = (width() + BLOCK_SIZE - 1) / BLOCK_SIZE; // ceil(width/BS)
+		int subHeight = (height() + BLOCK_SIZE - 1) / BLOCK_SIZE; // ceil(height/BS)
+		auto blackPoints =
+			CalculateBlackPoints(luminances, subWidth, subHeight, width(), height(), _buffer.rowStride());
+
+		return CalculateMatrix(luminances, subWidth, subHeight, width(), height(), _buffer.rowStride(), blackPoints);
+#endif
+	} else {
+		// If the image is too small, fall back to the global histogram approach.
+		return GlobalHistogramBinarizer::getBlackMatrix();
+	}
+}
+
+} // ZXing