src/cam/meson.build

/* SPDX-License-Identifier: LGPL-2.1-or-later */
/*
 * Copyright (C) 2021, Ideas On Board
 *
 * ipu3_awb.cpp - AWB control algorithm
 */
#include "ipu3_awb.h"

#include <cmath>
#include <numeric>
#include <unordered_map>

#include "libcamera/internal/log.h"

namespace libcamera {

namespace ipa::ipu3 {

LOG_DEFINE_CATEGORY(IPU3Awb)

static constexpr uint32_t kMinZonesCounted = 16;
static constexpr uint32_t kMinGreenLevelInZone = 32;

/**
 * \struct IspStatsRegion
 * \brief RGB statistics for a given region
 *
 * The IspStatsRegion structure is intended to abstract the ISP specific
 * statistics and use an agnostic algorithm to compute AWB.
 *
 * \var IspStatsRegion::counted
 * \brief Number of pixels used to calculate the sums
 *
 * \var IspStatsRegion::uncounted
 * \brief Remaining number of pixels in the region
 *
 * \var IspStatsRegion::rSum
 * \brief Sum of the red values in the region
 *
 * \var IspStatsRegion::gSum
 * \brief Sum of the green values in the region
 *
 * \var IspStatsRegion::bSum
 * \brief Sum of the blue values in the region
 */

/**
 * \struct AwbStatus
 * \brief AWB parameters calculated
 *
 * The AwbStatus structure is intended to store the AWB
 * parameters calculated by the algorithm
 *
 * \var AwbStatus::temperatureK
 * \brief Color temperature calculated
 *
 * \var AwbStatus::redGain
 * \brief Gain calculated for the red channel
 *
 * \var AwbStatus::greenGain
 * \brief Gain calculated for the green channel
 *
 * \var AwbStatus::blueGain
 * \brief Gain calculated for the blue channel
 */

/**
 * \struct Ipu3AwbCell
 * \brief Memory layout for each cell in AWB metadata
 *
 * The Ipu3AwbCell structure is used to get individual values
 * such as red average or saturation ratio in a particular cell.
 *
 * \var Ipu3AwbCell::greenRedAvg
 * \brief Green average for red lines in the cell
 *
 * \var Ipu3AwbCell::redAvg
 * \brief Red average in the cell
 *
 * \var Ipu3AwbCell::blueAvg
 * \brief blue average in the cell
 *
 * \var Ipu3AwbCell::greenBlueAvg
 * \brief Green average for blue lines
 *
 * \var Ipu3AwbCell::satRatio
 * \brief Saturation ratio in the cell
 *
 * \var Ipu3AwbCell::padding
 * \brief array of unused bytes for padding
 */

/* Default settings for Bayer noise reduction replicated from the Kernel */
static const struct ipu3_uapi_bnr_static_config imguCssBnrDefaults = {
	.wb_gains = { 16, 16, 16, 16 },
	.wb_gains_thr = { 255, 255, 255, 255 },
	.thr_coeffs = { 1700, 0, 31, 31, 0, 16 },
	.thr_ctrl_shd = { 26, 26, 26, 26 },
	.opt_center{ -648, 0, -366, 0 },
	.lut = {
		{ 17, 23, 28, 32, 36, 39, 42, 45,
		  48, 51, 53, 55, 58, 60, 62, 64,
		  66, 68, 70, 72, 73, 75, 77, 78,
		  80, 82, 83, 85, 86, 88, 89, 90 } },
	.bp_ctrl = { 20, 0, 1, 40, 0, 6, 0, 6, 0 },
	.dn_detect_ctrl{ 9, 3, 4, 0, 8, 0, 1, 1, 1, 1, 0 },
	.column_size = 1296,
	.opt_center_sqr = { 419904, 133956 },
};

/* Default settings for Auto White Balance replicated from the Kernel*/
static const struct ipu3_uapi_awb_config_s imguCssAwbDefaults = {
	.rgbs_thr_gr = 8191,
	.rgbs_thr_r = 8191,
	.rgbs_thr_gb = 8191,
	.rgbs_thr_b = 8191 | IPU3_UAPI_AWB_RGBS_THR_B_EN | IPU3_UAPI_AWB_RGBS_THR_B_INCL_SAT,
	.grid = {
		.width = 160,
		.height = 36,
		.block_width_log2 = 3,
		.block_height_log2 = 4,
		.height_per_slice = 1, /* Overridden by kernel. */
		.x_start = 0,
		.y_start = 0,
		.x_end = 0,
		.y_end = 0,
	},
};

/* Default color correction matrix defined as an identity matrix */
static const struct ipu3_uapi_ccm_mat_config imguCssCcmDefault = {
	8191, 0, 0, 0,
	0, 8191, 0, 0,
	0, 0, 8191, 0
};

IPU3Awb::IPU3Awb()
	: Algorithm()
{
	asyncResults_.blueGain = 1.0;
	asyncResults_.greenGain = 1.0;
	asyncResults_.redGain = 1.0;
	asyncResults_.temperatureK = 4500;
}

IPU3Awb::~IPU3Awb()
{
}

void IPU3Awb::initialise(ipu3_uapi_params &params, const Size &bdsOutputSize, struct ipu3_uapi_grid_config &bdsGrid)
{
	params.use.acc_awb = 1;
	params.acc_param.awb.config = imguCssAwbDefaults;

	awbGrid_ = bdsGrid;
	params.acc_param.awb.config.grid = awbGrid_;

	params.use.acc_bnr = 1;
	params.acc_param.bnr = imguCssBnrDefaults;
	/**
	 * Optical center is column (respectively row) startminus X (respectively Y) center.
	 * For the moment use BDS as a first approximation, but it should
	 * be calculated based on Shading (SHD) parameters.
	 */
	params.acc_param.bnr.column_size = bdsOutputSize.width;
	params.acc_param.bnr.opt_center.x_reset = awbGrid_.x_start - (bdsOutputSize.width / 2);
	params.acc_param.bnr.opt_center.y_reset = awbGrid_.y_start - (bdsOutputSize.height / 2);
	params.acc_param.bnr.opt_center_sqr.x_sqr_reset = params.acc_param.bnr.opt_center.x_reset
							* params.acc_param.bnr.opt_center.x_reset;
	params.acc_param.bnr.opt_center_sqr.y_sqr_reset = params.acc_param.bnr.opt_center.y_reset
							* params.acc_param.bnr.opt_center.y_reset;

	params.use.acc_ccm = 1;
	params.acc_param.ccm = imguCssCcmDefault;

	params.use.acc_gamma = 1;
	params.acc_param.gamma.gc_ctrl.enable = 1;

	zones_.reserve(kAwbStatsSizeX * kAwbStatsSizeY);
}

/**
 * The function estimates the correlated color temperature using
 * from RGB color space input.
 * In physics and color science, the Planckian locus or black body locus is
 * the path or locus that the color of an incandescent black body would take
 * in a particular chromaticity space as the blackbody temperature changes.
 *
 * If a narrow range of color temperatures is considered (those encapsulating
 * daylight being the most practical case) one can approximate the Planckian
 * locus in order to calculate the CCT in terms of chromaticity coordinates.
 *
 * More detailed information can be found in:
 * https://en.wikipedia.org/wiki/Color_temperature#Approximation
 */
uint32_t IPU3Awb::estimateCCT(double red, double green, double blue)
{
	/* Convert the RGB values to CIE tristimulus values (XYZ) */
	double X = (-0.14282) * (red) + (1.54924) * (green) + (-0.95641) * (blue);
	double Y = (-0.32466) * (red) + (1.57837) * (green) + (-0.73191) * (blue);
	double Z = (-0.68202) * (red) + (0.77073) * (green) + (0.56332) * (blue);

	/* Calculate the normalized chromaticity values */
	double x = X / (X + Y + Z);
	double y = Y / (X + Y + Z);

	/* Calculate CCT */
	double n = (x - 0.3320) / (0.1858 - y);
	return 449 * n * n * n + 3525 * n * n + 6823.3 * n + 5520.33;
}

/* Generate an RGB vector with the average values for each region */
void IPU3Awb::generateZones(std::vector<RGB> &zones)
{
	for (unsigned int i = 0; i < kAwbStatsSizeX * kAwbStatsSizeY; i++) {
		RGB zone;
		double counted = awbStats_[i].counted;
		if (counted >= kMinZonesCounted) {
			zone.G = awbStats_[i].gSum / counted;
			if (zone.G >= kMinGreenLevelInZone) {
				zone.R = awbStats_[i].rSum / counted;
				zone.B = awbStats_[i].bSum / counted;
				zones.push_back(zone);
			}
		}
	}
}

/* Translate the IPU3 statistics into the default statistics region array */
void IPU3Awb::generateAwbStats(const ipu3_uapi_stats_3a *stats)
{
	uint32_t regionWidth = round(awbGrid_.width / static_cast<double>(kAwbStatsSizeX));
	uint32_t regionHeight = round(awbGrid_.height / static_cast<double>(kAwbStatsSizeY));

	/*
	 * Generate a (kAwbStatsSizeX x kAwbStatsSizeY) array from the IPU3 grid which is
	 * (awbGrid_.width x awbGrid_.height).
	 */
	for (unsigned int j = 0; j < kAwbStatsSizeY * regionHeight; j++) {
		for (unsigned int i = 0; i < kAwbStatsSizeX * regionWidth; i++) {
			uint32_t cellPosition = j * awbGrid_.width + i;
			uint32_t cellX = (cellPosition / regionWidth) % kAwbStatsSizeX;
			uint32_t cellY = ((cellPosition / awbGrid_.width) / regionHeight) % kAwbStatsSizeY;

			uint32_t awbRegionPosition = cellY * kAwbStatsSizeX + cellX;
			cellPosition *= 8;

			/* Cast the initial IPU3 structure to simplify the reading */
			Ipu3AwbCell *currentCell = reinterpret_cast<Ipu3AwbCell *>(const_cast<uint8_t *>(&stats->awb_raw_buffer.meta_data[cellPosition]));
			if (currentCell->satRatio == 0) {
				/* The cell is not saturated, use the current cell */
				awbStats_[awbRegionPosition].counted++;
				uint32_t greenValue = currentCell->greenRedAvg + currentCell->greenBlueAvg;
				awbStats_[awbRegionPosition].gSum += greenValue / 2;
				awbStats_[awbRegionPosition].rSum += currentCell->redAvg;
				awbStats_[awbRegionPosition].bSum += currentCell->blueAvg;
			}
		}
	}
}

void IPU3Awb::clearAwbStats()
{
	for (unsigned int i = 0; i < kAwbStatsSizeX * kAwbStatsSizeY; i++) {
		awbStats_[i].bSum = 0;
		awbStats_[i].rSum = 0;
		awbStats_[i].gSum = 0;
		awbStats_[i].counted = 0;
		awbStats_[i].uncounted = 0;
	}
}

void IPU3Awb::awbGreyWorld()
{
	LOG(IPU3Awb, Debug) << "Grey world AWB";
	/*
	 * Make a separate list of the derivatives for each of red and blue, so
	 * that we can sort them to exclude the extreme gains. We could
	 * consider some variations, such as normalising all the zones first, or
	 * doing an L2 average etc.
	 */
	std::vector<RGB> &redDerivative(zones_);
	std::vector<RGB> blueDerivative(redDerivative);
	std::sort(redDerivative.begin(), redDerivative.end(),
		  [](RGB const &a, RGB const &b) {
			  return a.G * b.R < b.G * a.R;
		  });
	std::sort(blueDerivative.begin(), blueDerivative.end(),
		  [](RGB const &a, RGB const &b) {
			  return a.G * b.B < b.G * a.B;
		  });

	/* Average the middle half of the values. */
	int discard = redDerivative.size() / 4;

	RGB sumRed(0, 0, 0);
	RGB sumBlue(0, 0, 0);
	for (auto ri = redDerivative.begin() + discard,
		  bi = blueDerivative.begin() + discard;
	     ri != redDerivative.end() - discard; ri++, bi++)
		sumRed += *ri, sumBlue += *bi;

	double redGain = sumRed.G / (sumRed.R + 1),
	       blueGain = sumBlue.G / (sumBlue.B + 1);

	/* Color temperature is not relevant in Grey world but still useful to estimate it :-) */
	asyncResults_.temperatureK = estimateCCT(sumRed.R, sumRed.G, sumBlue.B);
	asyncResults_.redGain = redGain;
	asyncResults_.greenGain = 1.0;
	asyncResults_.blueGain = blueGain;
}

void IPU3Awb::calculateWBGains(const ipu3_uapi_stats_3a *stats)
{
	ASSERT(stats->stats_3a_status.awb_en);
	zones_.clear();
	clearAwbStats();
	generateAwbStats(stats);
	generateZones(zones_);
	LOG(IPU3Awb, Debug) << "Valid zones: " << zones_.size();
Age	Commit message (Expand)	Author
2019-05-25	cam: capture: Break out capture to a new class	Niklas Söderlund
2019-05-23	meson: Create and use a dependency for libcamera and its headers	Laurent Pinchart
2019-04-18	Install the cam and qcam utilities	Laurent Pinchart
2019-02-06	cam: Add BufferWriter helper	Niklas Söderlund
2019-01-25	cam: Add event loop	Laurent Pinchart
2019-01-22	cam: Extract option parser to separate file	Laurent Pinchart
2019-01-22	cam: add utility to control cameras	Niklas Söderlund