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ipa: rkisp1: Introduce AGC
Now that we have IPAContext and Algorithm, we can implement a simple AGC based on the IPU3 one. It is very similar, except that there is no histogram used for an inter quantile mean. The RkISP1 is returning a 5x5 array (for V10) of luminance means. Estimating the relative luminance is thus a simple mean of all the blocks already calculated by the ISP. Signed-off-by: Jean-Michel Hautbois <jeanmichel.hautbois@ideasonboard.com> Reviewed-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com> Reviewed-by: Kieran Bingham <kieran.bingham@ideasonboard.com>
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src/ipa/rkisp1/algorithms/agc.cpp
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src/ipa/rkisp1/algorithms/agc.cpp
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/* SPDX-License-Identifier: LGPL-2.1-or-later */
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/*
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* Copyright (C) 2021, Ideas On Board
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*
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* agc.cpp - AGC/AEC mean-based control algorithm
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*/
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#include "agc.h"
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#include <algorithm>
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#include <chrono>
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#include <cmath>
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#include <libcamera/base/log.h>
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#include <libcamera/ipa/core_ipa_interface.h>
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/**
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* \file agc.h
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*/
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namespace libcamera {
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using namespace std::literals::chrono_literals;
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namespace ipa::rkisp1::algorithms {
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/**
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* \class Agc
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* \brief A mean-based auto-exposure algorithm
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*/
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LOG_DEFINE_CATEGORY(RkISP1Agc)
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/* Limits for analogue gain values */
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static constexpr double kMinAnalogueGain = 1.0;
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static constexpr double kMaxAnalogueGain = 8.0;
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/* \todo Honour the FrameDurationLimits control instead of hardcoding a limit */
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static constexpr utils::Duration kMaxShutterSpeed = 60ms;
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/* Number of frames to wait before calculating stats on minimum exposure */
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static constexpr uint32_t kNumStartupFrames = 10;
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/*
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* Relative luminance target.
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*
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* It's a number that's chosen so that, when the camera points at a grey
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* target, the resulting image brightness is considered right.
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*
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* \todo Why is the value different between IPU3 and RkISP1 ?
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*/
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static constexpr double kRelativeLuminanceTarget = 0.4;
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Agc::Agc()
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: frameCount_(0), filteredExposure_(0s)
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{
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}
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/**
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* \brief Configure the AGC given a configInfo
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* \param[in] context The shared IPA context
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* \param[in] configInfo The IPA configuration data
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*
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* \return 0
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*/
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int Agc::configure(IPAContext &context,
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[[maybe_unused]] const IPACameraSensorInfo &configInfo)
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{
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/* Configure the default exposure and gain. */
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context.frameContext.agc.gain = std::max(context.configuration.agc.minAnalogueGain, kMinAnalogueGain);
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context.frameContext.agc.exposure = 10ms / context.configuration.sensor.lineDuration;
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/*
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* According to the RkISP1 documentation:
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* - versions < V12 have RKISP1_CIF_ISP_AE_MEAN_MAX_V10 entries,
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* - versions >= V12 have RKISP1_CIF_ISP_AE_MEAN_MAX_V12 entries.
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*/
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if (context.configuration.hw.revision < RKISP1_V12)
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numCells_ = RKISP1_CIF_ISP_AE_MEAN_MAX_V10;
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else
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numCells_ = RKISP1_CIF_ISP_AE_MEAN_MAX_V12;
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/* \todo Use actual frame index by populating it in the frameContext. */
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frameCount_ = 0;
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return 0;
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}
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/**
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* \brief Apply a filter on the exposure value to limit the speed of changes
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* \param[in] exposureValue The target exposure from the AGC algorithm
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*
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* The speed of the filter is adaptive, and will produce the target quicker
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* during startup, or when the target exposure is within 20% of the most recent
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* filter output.
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*
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* \return The filtered exposure
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*/
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utils::Duration Agc::filterExposure(utils::Duration exposureValue)
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{
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double speed = 0.2;
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/* Adapt instantly if we are in startup phase. */
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if (frameCount_ < kNumStartupFrames)
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speed = 1.0;
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/*
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* If we are close to the desired result, go faster to avoid making
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* multiple micro-adjustments.
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* \todo Make this customisable?
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*/
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if (filteredExposure_ < 1.2 * exposureValue &&
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filteredExposure_ > 0.8 * exposureValue)
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speed = sqrt(speed);
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filteredExposure_ = speed * exposureValue +
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filteredExposure_ * (1.0 - speed);
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LOG(RkISP1Agc, Debug) << "After filtering, exposure " << filteredExposure_;
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return filteredExposure_;
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}
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/**
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* \brief Estimate the new exposure and gain values
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* \param[inout] frameContext The shared IPA frame Context
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* \param[in] yGain The gain calculated on the current brightness level
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*/
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void Agc::computeExposure(IPAContext &context, double yGain)
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{
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IPASessionConfiguration &configuration = context.configuration;
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IPAFrameContext &frameContext = context.frameContext;
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/* Get the effective exposure and gain applied on the sensor. */
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uint32_t exposure = frameContext.sensor.exposure;
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double analogueGain = frameContext.sensor.gain;
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utils::Duration minShutterSpeed = configuration.agc.minShutterSpeed;
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utils::Duration maxShutterSpeed = std::min(configuration.agc.maxShutterSpeed,
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kMaxShutterSpeed);
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double minAnalogueGain = std::max(configuration.agc.minAnalogueGain,
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kMinAnalogueGain);
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double maxAnalogueGain = std::min(configuration.agc.maxAnalogueGain,
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kMaxAnalogueGain);
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/* Consider within 1% of the target as correctly exposed. */
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if (std::abs(yGain - 1.0) < 0.01)
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return;
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/* extracted from Rpi::Agc::computeTargetExposure. */
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/* Calculate the shutter time in seconds. */
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utils::Duration currentShutter = exposure * configuration.sensor.lineDuration;
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/*
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* Update the exposure value for the next computation using the values
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* of exposure and gain really used by the sensor.
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*/
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utils::Duration effectiveExposureValue = currentShutter * analogueGain;
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LOG(RkISP1Agc, Debug) << "Actual total exposure " << currentShutter * analogueGain
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<< " Shutter speed " << currentShutter
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<< " Gain " << analogueGain
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<< " Needed ev gain " << yGain;
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/*
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* Calculate the current exposure value for the scene as the latest
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* exposure value applied multiplied by the new estimated gain.
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*/
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utils::Duration exposureValue = effectiveExposureValue * yGain;
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/* Clamp the exposure value to the min and max authorized. */
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utils::Duration maxTotalExposure = maxShutterSpeed * maxAnalogueGain;
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exposureValue = std::min(exposureValue, maxTotalExposure);
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LOG(RkISP1Agc, Debug) << "Target total exposure " << exposureValue
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<< ", maximum is " << maxTotalExposure;
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/*
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* Divide the exposure value as new exposure and gain values.
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* \todo estimate if we need to desaturate
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*/
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exposureValue = filterExposure(exposureValue);
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/*
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* Push the shutter time up to the maximum first, and only then
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* increase the gain.
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*/
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utils::Duration shutterTime = std::clamp<utils::Duration>(exposureValue / minAnalogueGain,
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minShutterSpeed, maxShutterSpeed);
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double stepGain = std::clamp(exposureValue / shutterTime,
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minAnalogueGain, maxAnalogueGain);
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LOG(RkISP1Agc, Debug) << "Divided up shutter and gain are "
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<< shutterTime << " and "
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<< stepGain;
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/* Update the estimated exposure and gain. */
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frameContext.agc.exposure = shutterTime / configuration.sensor.lineDuration;
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frameContext.agc.gain = stepGain;
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}
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/**
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* \brief Estimate the relative luminance of the frame with a given gain
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* \param[in] ae The RkISP1 statistics and ISP results
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* \param[in] gain The gain to apply to the frame
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*
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* This function estimates the average relative luminance of the frame that
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* would be output by the sensor if an additional \a gain was applied.
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*
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* The estimation is based on the AE statistics for the current frame. Y
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* averages for all cells are first multiplied by the gain, and then saturated
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* to approximate the sensor behaviour at high brightness values. The
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* approximation is quite rough, as it doesn't take into account non-linearities
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* when approaching saturation. In this case, saturating after the conversion to
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* YUV doesn't take into account the fact that the R, G and B components
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* contribute differently to the relative luminance.
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*
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* \todo Have a dedicated YUV algorithm ?
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*
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* The values are normalized to the [0.0, 1.0] range, where 1.0 corresponds to a
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* theoretical perfect reflector of 100% reference white.
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*
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* More detailed information can be found in:
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* https://en.wikipedia.org/wiki/Relative_luminance
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*
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* \return The relative luminance
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*/
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double Agc::estimateLuminance(const rkisp1_cif_isp_ae_stat *ae,
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double gain)
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{
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double ySum = 0.0;
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/* Sum the averages, saturated to 255. */
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for (unsigned int aeCell = 0; aeCell < numCells_; aeCell++)
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ySum += std::min(ae->exp_mean[aeCell] * gain, 255.0);
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/* \todo Weight with the AWB gains */
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return ySum / numCells_ / 255;
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}
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/**
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* \brief Process RkISP1 statistics, and run AGC operations
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* \param[in] context The shared IPA context
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* \param[in] stats The RKISP1 statistics and ISP results
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*
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* Identify the current image brightness, and use that to estimate the optimal
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* new exposure and gain for the scene.
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*/
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void Agc::process(IPAContext &context, const rkisp1_stat_buffer *stats)
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{
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const rkisp1_cif_isp_stat *params = &stats->params;
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ASSERT(stats->meas_type & RKISP1_CIF_ISP_STAT_AUTOEXP);
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const rkisp1_cif_isp_ae_stat *ae = ¶ms->ae;
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/*
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* Estimate the gain needed to achieve a relative luminance target. To
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* account for non-linearity caused by saturation, the value needs to be
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* estimated in an iterative process, as multiplying by a gain will not
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* increase the relative luminance by the same factor if some image
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* regions are saturated.
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*/
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double yGain = 1.0;
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double yTarget = kRelativeLuminanceTarget;
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for (unsigned int i = 0; i < 8; i++) {
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double yValue = estimateLuminance(ae, yGain);
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double extra_gain = std::min(10.0, yTarget / (yValue + .001));
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yGain *= extra_gain;
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LOG(RkISP1Agc, Debug) << "Y value: " << yValue
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<< ", Y target: " << yTarget
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<< ", gives gain " << yGain;
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if (extra_gain < 1.01)
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break;
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}
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computeExposure(context, yGain);
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frameCount_++;
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}
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} /* namespace ipa::rkisp1::algorithms */
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} /* namespace libcamera */
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