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AgeCommit message (Expand)Author
2020-03-18libcamera: framebuffer_allocator: Lift camera restrictions on allocatorLaurent Pinchart
2020-03-18libcamera: PixelFormat: Turn into a classNiklas Söderlund
2020-03-18libcamera: Use PixelFormat instead of unsigned int where appropriateNiklas Söderlund
2020-03-18cam: Create stream names after configuring the cameraNiklas Söderlund
2020-03-08cam: Link against libatomic if neededLaurent Pinchart
2020-03-06cam: Add option to list camera propertiesJacopo Mondi
2020-01-12libcamera: camera: Remove the prepared stateNiklas Söderlund
2020-01-12cam: Cache buffer memory mappingNiklas Söderlund
2020-01-12libcamera: Switch to FrameBuffer interfaceNiklas Söderlund
2020-01-12libcamera: buffer: Move captured metadata to FrameMetadataNiklas Söderlund
2020-01-12libcamera: request: In addBuffer() do not fetch stream from BufferNiklas Söderlund
2020-01-12libcamera: buffer: Switch from Plane to FrameBuffer::PlaneNiklas Söderlund
2019-12-16libcamera: Remove buffer index from loggingNiklas Söderlund
2019-11-26cam: options: Fix unitialized variable warningLaurent Pinchart
2019-11-20cam: Store camera as shared pointer everywhereNiklas Söderlund
2019-11-20cam: BufferWriter: Use the libcamera namespaceNiklas Söderlund
2019-11-19libcamera: camera: Remove explicit stream to buffer map in requestCompleted s...Niklas Söderlund
2019-11-08libcamera: Remove unneeded semicolonsLaurent Pinchart
2019-10-26cam: capture: remove unused local variablePaul Elder
2019-10-23libcamera: Standardise on C compatibility headersLaurent Pinchart
2019-09-14libcamera: Switch to the std::chrono APILaurent Pinchart
2019-08-19libcamera: camera_manager: Construct CameraManager instances manuallyLaurent Pinchart
2019-07-14libcamera: buffer: Add an accessor to the BufferMemoryLaurent Pinchart
2019-07-14libcamera: stream: Shorten access to the bufferPoolJacopo Mondi
2019-07-14libcamera: Stop using Stream::bufferPool to get the number of buffersLaurent Pinchart
2019-07-14libcamera: buffer: Split memory information to BufferMemoryLaurent Pinchart
2019-06-25cam: capture: Stop stream when queueRequest() failsHelen Koike
2019-06-19cam: Support base 16 and base 8 when parsing integer optionsLaurent Pinchart
2019-06-19cam: Add --info option to print information about stream(s)Niklas Söderlund
2019-06-19cam: Validate camera configurationNiklas Söderlund
2019-06-19cam: Move camera configuration preparation to CamAppNiklas Söderlund
2019-06-18cam: Allow selecting cameras by indexLaurent Pinchart
2019-06-10cam: Fix cam --help crashNiklas Söderlund
2019-05-25cam: Add CamApp classNiklas Söderlund
2019-05-25cam: capture: Break out capture to a new classNiklas Söderlund
2019-05-23meson: Create and use a dependency for libcamera and its headersLaurent Pinchart
2019-05-23cam: Rename conf variable referring to command line option to optLaurent Pinchart
2019-05-23libcamera: camera: Add a validation API to the CameraConfiguration classLaurent Pinchart
2019-05-23libcamera: camera: Return a pointer from generateConfiguration()Laurent Pinchart
2019-05-23libcamera: Refactor the camera configuration storage and APILaurent Pinchart
2019-05-23libcamera: Use stream roles directly instead of StreamUsageLaurent Pinchart
2019-05-23libcamera: camera: Rename configureStreams() and streamConfiguration()Laurent Pinchart
2019-04-30libcamera: Use the Size class through libcameraLaurent Pinchart
2019-04-26cam: options: Fix string concatenationLaurent Pinchart
2019-04-26cam: options: Don't initialise variable-length arraysLaurent Pinchart
2019-04-18Install the cam and qcam utilitiesLaurent Pinchart
2019-04-09cam: Allow cameras with more than one streamNiklas Söderlund
2019-04-09cam: Extend request completion handler to deal with multiple streamsNiklas Söderlund
2019-04-09cam: Add support to specify multiple stream configurations with rolesNiklas Söderlund
2019-04-09cam: Extend BufferWriter to include a stream name in file pathNiklas Söderlund
generated by cgit v1.2.1 (git 2.18.0) at 2025-02-17 18:04:48 +0000
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/* SPDX-License-Identifier: LGPL-2.1-or-later */
/*
 * Copyright (C) 2021, Ideas On Board
 *
 * awb.cpp - AWB control algorithm
 */
#include "awb.h"

#include <algorithm>
#include <cmath>

#include <libcamera/base/log.h>

#include <libcamera/control_ids.h>

/**
 * \file awb.h
 */

namespace libcamera {

namespace ipa::ipu3::algorithms {

LOG_DEFINE_CATEGORY(IPU3Awb)

/*
 * When zones are used for the grey world algorithm, they are only considered if
 * their average green value is at least 16/255 (after black level subtraction)
 * to exclude zones that are too dark and don't provide relevant colour
 * information (on the opposite side of the spectrum, saturated regions are
 * excluded by the ImgU statistics engine).
 */
static constexpr uint32_t kMinGreenLevelInZone = 16;

/*
 * Minimum proportion of non-saturated cells in a zone for the zone to be used
 * by the AWB algorithm.
 */
static constexpr double kMaxCellSaturationRatio = 0.8;

/*
 * Maximum ratio of saturated pixels in a cell for the cell to be considered
 * non-saturated and counted by the AWB algorithm.
 */
static constexpr uint32_t kMinCellsPerZoneRatio = 255 * 90 / 100;

/**
 * \struct Accumulator
 * \brief RGB statistics for a given zone
 *
 * Accumulate red, green and blue values for each non-saturated item over a
 * zone. Items can for instance be pixels, but also the average of groups of
 * pixels, depending on who uses the accumulator.
 * \todo move this description and structure into a common header
 *
 * Zones which are saturated beyond the threshold defined in
 * ipu3_uapi_awb_config_s are not included in the average.
 *
 * \var Accumulator::counted
 * \brief Number of unsaturated cells used to calculate the sums
 *
 * \var Accumulator::sum
 * \brief A structure containing the average red, green and blue sums
 *
 * \var Accumulator::sum.red
 * \brief Sum of the average red values of each unsaturated cell in the zone
 *
 * \var Accumulator::sum.green
 * \brief Sum of the average green values of each unsaturated cell in the zone
 *
 * \var Accumulator::sum.blue
 * \brief Sum of the average blue values of each unsaturated cell in the zone
 */

/**
 * \struct Awb::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
 */

/* 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 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
};

/**
 * \class Awb
 * \brief A Grey world white balance correction algorithm
 *
 * The Grey World algorithm assumes that the scene, in average, is neutral grey.
 * Reference: Lam, Edmund & Fung, George. (2008). Automatic White Balancing in
 * Digital Photography. 10.1201/9781420054538.ch10.
 *
 * The IPU3 generates statistics from the Bayer Down Scaler output into a grid
 * defined in the ipu3_uapi_awb_config_s structure.
 *
 * - Cells are defined in Pixels
 * - Zones are defined in Cells
 *
 *                             80 cells
 *            /───────────── 1280 pixels ───────────\
 *                             16 zones
 *             16
 *           ┌────┬────┬────┬────┬────┬─  ──────┬────┐   \
 *           │Cell│    │    │    │    │    |    │    │   │
 *        16 │ px │    │    │    │    │    |    │    │   │
 *           ├────┼────┼────┼────┼────┼─  ──────┼────┤   │
 *           │    │    │    │    │    │    |    │    │
 *           │    │    │    │    │    │    |    │    │   7
 *           │ ── │ ── │ ── │ ── │ ── │ ──  ── ─┤ ── │ 1 2 4
 *           │    │    │    │    │    │    |    │    │ 2 0 5
 *
 *           │    │    │    │    │    │    |    │    │ z p c
 *           ├────┼────┼────┼────┼────┼─  ──────┼────┤ o i e
 *           │    │    │    │    │    │    |    │    │ n x l
 *           │                        │    |    │    │ e e l
 *           ├───                  ───┼─  ──────┼────┤ s l s
 *           │                        │    |    │    │   s
 *           │                        │    |    │    │
 *           ├───   Zone of Cells  ───┼─  ──────┼────┤   │
 *           │        (5 x 4)         │    |    │    │   │
 *           │                        │    |    │    │   │
 *           ├──                   ───┼─  ──────┼────┤   │
 *           │                   │    │    |    │    │   │
 *           │    │    │    │    │    │    |    │    │   │
 *           └────┴────┴────┴────┴────┴─  ──────┴────┘   /
 *
 *
 * In each cell, the ImgU computes for each colour component the average of all
 * unsaturated pixels (below a programmable threshold). It also provides the
 * ratio of saturated pixels in the cell.
 *
 * The AWB algorithm operates on a coarser grid, made by grouping cells from the
 * hardware grid into zones. The number of zones is fixed to \a kAwbStatsSizeX x
 * \a kAwbStatsSizeY. For example, a frame of 1280x720 is divided into 80x45
 * cells of [16x16] pixels and 16x12 zones of [5x4] cells each
 * (\a kAwbStatsSizeX=16 and \a kAwbStatsSizeY=12). If the number of cells isn't
 * an exact multiple of the number of zones, the right-most and bottom-most
 * cells are ignored. The grid configuration is computed by
 * IPAIPU3::calculateBdsGrid().
 *
 * Before calculating the gains, the algorithm aggregates the cell averages for
 * each zone in generateAwbStats(). Cells that have a too high ratio of
 * saturated pixels are ignored, and only zones that contain enough
 * non-saturated cells are then used by the algorithm.
 *
 * The Grey World algorithm will then estimate the red and blue gains to apply, and
 * store the results in the metadata. The green gain is always set to 1.
 */

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

	zones_.reserve(kAwbStatsSizeX * kAwbStatsSizeY);
}

Awb::~Awb() = default;

/**
 * \copydoc libcamera::ipa::Algorithm::configure
 */
int Awb::configure(IPAContext &context,
		   [[maybe_unused]] const IPAConfigInfo &configInfo)
{
	const ipu3_uapi_grid_config &grid = context.configuration.grid.bdsGrid;
	stride_ = context.configuration.grid.stride;

	cellsPerZoneX_ = std::round(grid.width / static_cast<double>(kAwbStatsSizeX));
	cellsPerZoneY_ = std::round(grid.height / static_cast<double>(kAwbStatsSizeY));

	/*
	 * Configure the minimum proportion of cells counted within a zone
	 * for it to be relevant for the grey world algorithm.
	 * \todo This proportion could be configured.
	 */
	cellsPerZoneThreshold_ = cellsPerZoneX_ * cellsPerZoneY_ * kMaxCellSaturationRatio;
	LOG(IPU3Awb, Debug) << "Threshold for AWB is set to " << cellsPerZoneThreshold_;

	return 0;
}

constexpr uint16_t Awb::threshold(float value)
{
	/* AWB thresholds are in the range [0, 8191] */
	return value * 8191;
}

constexpr uint16_t Awb::gainValue(double gain)
{
	/*
	 * The colour gains applied by the BNR for the four channels (Gr, R, B
	 * and Gb) are expressed in the parameters structure as 16-bit integers
	 * that store a fixed-point U3.13 value in the range [0, 8[.
	 *
	 * The real gain value is equal to the gain parameter plus one, i.e.
	 *
	 * Pout = Pin * (1 + gain / 8192)
	 *
	 * where 'Pin' is the input pixel value, 'Pout' the output pixel value,
	 * and 'gain' the gain in the parameters structure as a 16-bit integer.
	 */
	return std::clamp((gain - 1.0) * 8192, 0.0, 65535.0);
}

/**
 * \copydoc libcamera::ipa::Algorithm::prepare
 */
void Awb::prepare(IPAContext &context,
		  [[maybe_unused]] const uint32_t frame,
		  [[maybe_unused]] IPAFrameContext &frameContext,
		  ipu3_uapi_params *params)
{
	/*
	 * Green saturation thresholds are reduced because we are using the
	 * green channel only in the exposure computation.
	 */
	params->acc_param.awb.config.rgbs_thr_r = threshold(1.0);
	params->acc_param.awb.config.rgbs_thr_gr = threshold(0.9);
	params->acc_param.awb.config.rgbs_thr_gb = threshold(0.9);
	params->acc_param.awb.config.rgbs_thr_b = threshold(1.0);

	/*
	 * Enable saturation inclusion on thr_b for ImgU to update the
	 * ipu3_uapi_awb_set_item->sat_ratio field.
	 */
	params->acc_param.awb.config.rgbs_thr_b |= IPU3_UAPI_AWB_RGBS_THR_B_INCL_SAT |
						   IPU3_UAPI_AWB_RGBS_THR_B_EN;

	const ipu3_uapi_grid_config &grid = context.configuration.grid.bdsGrid;

	params->acc_param.awb.config.grid = context.configuration.grid.bdsGrid;

	/*
	 * Optical center is column start (respectively row start) of the
	 * cell of interest minus its X center (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 = imguCssBnrDefaults;
	Size &bdsOutputSize = context.configuration.grid.bdsOutputSize;
	params->acc_param.bnr.column_size = bdsOutputSize.width;
	params->acc_param.bnr.opt_center.x_reset = grid.x_start - (bdsOutputSize.width / 2);
	params->acc_param.bnr.opt_center.y_reset = grid.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->acc_param.bnr.wb_gains.gr = gainValue(context.activeState.awb.gains.green);
	params->acc_param.bnr.wb_gains.r  = gainValue(context.activeState.awb.gains.red);
	params->acc_param.bnr.wb_gains.b  = gainValue(context.activeState.awb.gains.blue);
	params->acc_param.bnr.wb_gains.gb = gainValue(context.activeState.awb.gains.green);

	LOG(IPU3Awb, Debug) << "Color temperature estimated: " << asyncResults_.temperatureK;

	/* The CCM matrix may change when color temperature will be used */
	params->acc_param.ccm = imguCssCcmDefault;

	params->use.acc_awb = 1;
	params->use.acc_bnr = 1;
	params->use.acc_ccm = 1;
}

/**
 * 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 Awb::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 zone */
void Awb::generateZones()
{
	zones_.clear();

	for (unsigned int i = 0; i < kAwbStatsSizeX * kAwbStatsSizeY; i++) {
		RGB zone;
		double counted = awbStats_[i].counted;
		if (counted >= cellsPerZoneThreshold_) {
			zone.G = awbStats_[i].sum.green / counted;
			if (zone.G >= kMinGreenLevelInZone) {
				zone.R = awbStats_[i].sum.red / counted;
				zone.B = awbStats_[i].sum.blue / counted;
				zones_.push_back(zone);
			}
		}
	}
}

/* Translate the IPU3 statistics into the default statistics zone array */
void Awb::generateAwbStats(const ipu3_uapi_stats_3a *stats)
{
	/*
	 * Generate a (kAwbStatsSizeX x kAwbStatsSizeY) array from the IPU3 grid which is
	 * (grid.width x grid.height).
	 */
	for (unsigned int cellY = 0; cellY < kAwbStatsSizeY * cellsPerZoneY_; cellY++) {
		for (unsigned int cellX = 0; cellX < kAwbStatsSizeX * cellsPerZoneX_; cellX++) {
			uint32_t cellPosition = cellY * stride_ + cellX;
			uint32_t zoneX = cellX / cellsPerZoneX_;
			uint32_t zoneY = cellY / cellsPerZoneY_;

			uint32_t awbZonePosition = zoneY * kAwbStatsSizeX + zoneX;

			/* Cast the initial IPU3 structure to simplify the reading */
			const ipu3_uapi_awb_set_item *currentCell =
				reinterpret_cast<const ipu3_uapi_awb_set_item *>(
					&stats->awb_raw_buffer.meta_data[cellPosition]
				);

			/*
			 * Use cells which have less than 90%
			 * saturation as an initial means to include
			 * otherwise bright cells which are not fully
			 * saturated.
			 *
			 * \todo The 90% saturation rate may require
			 * further empirical measurements and
			 * optimisation during camera tuning phases.
			 */
			if (currentCell->sat_ratio <= kMinCellsPerZoneRatio) {
				/* The cell is not saturated, use the current cell */
				awbStats_[awbZonePosition].counted++;
				uint32_t greenValue = currentCell->Gr_avg + currentCell->Gb_avg;
				awbStats_[awbZonePosition].sum.green += greenValue / 2;
				awbStats_[awbZonePosition].sum.red += currentCell->R_avg;
				awbStats_[awbZonePosition].sum.blue += currentCell->B_avg;
			}
		}
	}
}

void Awb::clearAwbStats()
{
	for (unsigned int i = 0; i < kAwbStatsSizeX * kAwbStatsSizeY; i++) {
		awbStats_[i].sum.blue = 0;
		awbStats_[i].sum.red = 0;
		awbStats_[i].sum.green = 0;
		awbStats_[i].counted = 0;
	}
}

void Awb::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);

	/*
	 * Gain values are unsigned integer value ranging [0, 8) with 13 bit
	 * fractional part.
	 */
	redGain = std::clamp(redGain, 0.0, 65535.0 / 8192);
	blueGain = std::clamp(blueGain, 0.0, 65535.0 / 8192);

	asyncResults_.redGain = redGain;
	/* Hardcode the green gain to 1.0. */
	asyncResults_.greenGain = 1.0;
	asyncResults_.blueGain = blueGain;
}

void Awb::calculateWBGains(const ipu3_uapi_stats_3a *stats)
{
	ASSERT(stats->stats_3a_status.awb_en);

	clearAwbStats();
	generateAwbStats(stats);
	generateZones();

	LOG(IPU3Awb, Debug) << "Valid zones: " << zones_.size();

	if (zones_.size() > 10) {
		awbGreyWorld();
		LOG(IPU3Awb, Debug) << "Gain found for red: " << asyncResults_.redGain
				    << " and for blue: " << asyncResults_.blueGain;
	}
}

/**
 * \copydoc libcamera::ipa::Algorithm::process
 */
void Awb::process(IPAContext &context, [[maybe_unused]] const uint32_t frame,
		  [[maybe_unused]] IPAFrameContext &frameContext,
		  const ipu3_uapi_stats_3a *stats,
		  [[maybe_unused]] ControlList &metadata)
{
	calculateWBGains(stats);

	/*
	 * Gains are only recalculated if enough zones were detected.
	 * The results are cached, so if no results were calculated, we set the
	 * cached values from asyncResults_ here.
	 */
	context.activeState.awb.gains.blue = asyncResults_.blueGain;
	context.activeState.awb.gains.green = asyncResults_.greenGain;
	context.activeState.awb.gains.red = asyncResults_.redGain;
	context.activeState.awb.temperatureK = asyncResults_.temperatureK;

	metadata.set(controls::AwbEnable, true);
	metadata.set(controls::ColourGains, {
			static_cast<float>(context.activeState.awb.gains.red),
			static_cast<float>(context.activeState.awb.gains.blue)
		});
	metadata.set(controls::ColourTemperature,
		     context.activeState.awb.temperatureK);
}

REGISTER_IPA_ALGORITHM(Awb, "Awb")

} /* namespace ipa::ipu3::algorithms */

} /* namespace libcamera */
generated by cgit v1.2.1 (git 2.18.0) at 2025-02-17 18:04:48 +0000