From fea85f84c2ac940f1e149d1382216ab3da0b7703 Mon Sep 17 00:00:00 2001 From: Jean-Michel Hautbois Date: Fri, 19 Nov 2021 07:56:12 +0100 Subject: 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 Reviewed-by: Laurent Pinchart Reviewed-by: Kieran Bingham --- src/ipa/rkisp1/algorithms/agc.cpp | 285 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 285 insertions(+) create mode 100644 src/ipa/rkisp1/algorithms/agc.cpp (limited to 'src/ipa/rkisp1/algorithms/agc.cpp') diff --git a/src/ipa/rkisp1/algorithms/agc.cpp b/src/ipa/rkisp1/algorithms/agc.cpp new file mode 100644 index 00000000..2c222a4e --- /dev/null +++ b/src/ipa/rkisp1/algorithms/agc.cpp @@ -0,0 +1,285 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2021, Ideas On Board + * + * agc.cpp - AGC/AEC mean-based control algorithm + */ + +#include "agc.h" + +#include +#include +#include + +#include + +#include + +/** + * \file agc.h + */ + +namespace libcamera { + +using namespace std::literals::chrono_literals; + +namespace ipa::rkisp1::algorithms { + +/** + * \class Agc + * \brief A mean-based auto-exposure algorithm + */ + +LOG_DEFINE_CATEGORY(RkISP1Agc) + +/* Limits for analogue gain values */ +static constexpr double kMinAnalogueGain = 1.0; +static constexpr double kMaxAnalogueGain = 8.0; + +/* \todo Honour the FrameDurationLimits control instead of hardcoding a limit */ +static constexpr utils::Duration kMaxShutterSpeed = 60ms; + +/* Number of frames to wait before calculating stats on minimum exposure */ +static constexpr uint32_t kNumStartupFrames = 10; + +/* + * Relative luminance target. + * + * It's a number that's chosen so that, when the camera points at a grey + * target, the resulting image brightness is considered right. + * + * \todo Why is the value different between IPU3 and RkISP1 ? + */ +static constexpr double kRelativeLuminanceTarget = 0.4; + +Agc::Agc() + : frameCount_(0), filteredExposure_(0s) +{ +} + +/** + * \brief Configure the AGC given a configInfo + * \param[in] context The shared IPA context + * \param[in] configInfo The IPA configuration data + * + * \return 0 + */ +int Agc::configure(IPAContext &context, + [[maybe_unused]] const IPACameraSensorInfo &configInfo) +{ + /* Configure the default exposure and gain. */ + context.frameContext.agc.gain = std::max(context.configuration.agc.minAnalogueGain, kMinAnalogueGain); + context.frameContext.agc.exposure = 10ms / context.configuration.sensor.lineDuration; + + /* + * According to the RkISP1 documentation: + * - versions < V12 have RKISP1_CIF_ISP_AE_MEAN_MAX_V10 entries, + * - versions >= V12 have RKISP1_CIF_ISP_AE_MEAN_MAX_V12 entries. + */ + if (context.configuration.hw.revision < RKISP1_V12) + numCells_ = RKISP1_CIF_ISP_AE_MEAN_MAX_V10; + else + numCells_ = RKISP1_CIF_ISP_AE_MEAN_MAX_V12; + + /* \todo Use actual frame index by populating it in the frameContext. */ + frameCount_ = 0; + return 0; +} + +/** + * \brief Apply a filter on the exposure value to limit the speed of changes + * \param[in] exposureValue The target exposure from the AGC algorithm + * + * The speed of the filter is adaptive, and will produce the target quicker + * during startup, or when the target exposure is within 20% of the most recent + * filter output. + * + * \return The filtered exposure + */ +utils::Duration Agc::filterExposure(utils::Duration exposureValue) +{ + double speed = 0.2; + + /* Adapt instantly if we are in startup phase. */ + if (frameCount_ < kNumStartupFrames) + speed = 1.0; + + /* + * If we are close to the desired result, go faster to avoid making + * multiple micro-adjustments. + * \todo Make this customisable? + */ + if (filteredExposure_ < 1.2 * exposureValue && + filteredExposure_ > 0.8 * exposureValue) + speed = sqrt(speed); + + filteredExposure_ = speed * exposureValue + + filteredExposure_ * (1.0 - speed); + + LOG(RkISP1Agc, Debug) << "After filtering, exposure " << filteredExposure_; + + return filteredExposure_; +} + +/** + * \brief Estimate the new exposure and gain values + * \param[inout] frameContext The shared IPA frame Context + * \param[in] yGain The gain calculated on the current brightness level + */ +void Agc::computeExposure(IPAContext &context, double yGain) +{ + IPASessionConfiguration &configuration = context.configuration; + IPAFrameContext &frameContext = context.frameContext; + + /* Get the effective exposure and gain applied on the sensor. */ + uint32_t exposure = frameContext.sensor.exposure; + double analogueGain = frameContext.sensor.gain; + + utils::Duration minShutterSpeed = configuration.agc.minShutterSpeed; + utils::Duration maxShutterSpeed = std::min(configuration.agc.maxShutterSpeed, + kMaxShutterSpeed); + + double minAnalogueGain = std::max(configuration.agc.minAnalogueGain, + kMinAnalogueGain); + double maxAnalogueGain = std::min(configuration.agc.maxAnalogueGain, + kMaxAnalogueGain); + + /* Consider within 1% of the target as correctly exposed. */ + if (std::abs(yGain - 1.0) < 0.01) + return; + + /* extracted from Rpi::Agc::computeTargetExposure. */ + + /* Calculate the shutter time in seconds. */ + utils::Duration currentShutter = exposure * configuration.sensor.lineDuration; + + /* + * Update the exposure value for the next computation using the values + * of exposure and gain really used by the sensor. + */ + utils::Duration effectiveExposureValue = currentShutter * analogueGain; + + LOG(RkISP1Agc, Debug) << "Actual total exposure " << currentShutter * analogueGain + << " Shutter speed " << currentShutter + << " Gain " << analogueGain + << " Needed ev gain " << yGain; + + /* + * Calculate the current exposure value for the scene as the latest + * exposure value applied multiplied by the new estimated gain. + */ + utils::Duration exposureValue = effectiveExposureValue * yGain; + + /* Clamp the exposure value to the min and max authorized. */ + utils::Duration maxTotalExposure = maxShutterSpeed * maxAnalogueGain; + exposureValue = std::min(exposureValue, maxTotalExposure); + LOG(RkISP1Agc, Debug) << "Target total exposure " << exposureValue + << ", maximum is " << maxTotalExposure; + + /* + * Divide the exposure value as new exposure and gain values. + * \todo estimate if we need to desaturate + */ + exposureValue = filterExposure(exposureValue); + + /* + * Push the shutter time up to the maximum first, and only then + * increase the gain. + */ + utils::Duration shutterTime = std::clamp(exposureValue / minAnalogueGain, + minShutterSpeed, maxShutterSpeed); + double stepGain = std::clamp(exposureValue / shutterTime, + minAnalogueGain, maxAnalogueGain); + LOG(RkISP1Agc, Debug) << "Divided up shutter and gain are " + << shutterTime << " and " + << stepGain; + + /* Update the estimated exposure and gain. */ + frameContext.agc.exposure = shutterTime / configuration.sensor.lineDuration; + frameContext.agc.gain = stepGain; +} + +/** + * \brief Estimate the relative luminance of the frame with a given gain + * \param[in] ae The RkISP1 statistics and ISP results + * \param[in] gain The gain to apply to the frame + * + * This function estimates the average relative luminance of the frame that + * would be output by the sensor if an additional \a gain was applied. + * + * The estimation is based on the AE statistics for the current frame. Y + * averages for all cells are first multiplied by the gain, and then saturated + * to approximate the sensor behaviour at high brightness values. The + * approximation is quite rough, as it doesn't take into account non-linearities + * when approaching saturation. In this case, saturating after the conversion to + * YUV doesn't take into account the fact that the R, G and B components + * contribute differently to the relative luminance. + * + * \todo Have a dedicated YUV algorithm ? + * + * The values are normalized to the [0.0, 1.0] range, where 1.0 corresponds to a + * theoretical perfect reflector of 100% reference white. + * + * More detailed information can be found in: + * https://en.wikipedia.org/wiki/Relative_luminance + * + * \return The relative luminance + */ +double Agc::estimateLuminance(const rkisp1_cif_isp_ae_stat *ae, + double gain) +{ + double ySum = 0.0; + + /* Sum the averages, saturated to 255. */ + for (unsigned int aeCell = 0; aeCell < numCells_; aeCell++) + ySum += std::min(ae->exp_mean[aeCell] * gain, 255.0); + + /* \todo Weight with the AWB gains */ + + return ySum / numCells_ / 255; +} + +/** + * \brief Process RkISP1 statistics, and run AGC operations + * \param[in] context The shared IPA context + * \param[in] stats The RKISP1 statistics and ISP results + * + * Identify the current image brightness, and use that to estimate the optimal + * new exposure and gain for the scene. + */ +void Agc::process(IPAContext &context, const rkisp1_stat_buffer *stats) +{ + const rkisp1_cif_isp_stat *params = &stats->params; + ASSERT(stats->meas_type & RKISP1_CIF_ISP_STAT_AUTOEXP); + + const rkisp1_cif_isp_ae_stat *ae = ¶ms->ae; + + /* + * Estimate the gain needed to achieve a relative luminance target. To + * account for non-linearity caused by saturation, the value needs to be + * estimated in an iterative process, as multiplying by a gain will not + * increase the relative luminance by the same factor if some image + * regions are saturated. + */ + double yGain = 1.0; + double yTarget = kRelativeLuminanceTarget; + + for (unsigned int i = 0; i < 8; i++) { + double yValue = estimateLuminance(ae, yGain); + double extra_gain = std::min(10.0, yTarget / (yValue + .001)); + + yGain *= extra_gain; + LOG(RkISP1Agc, Debug) << "Y value: " << yValue + << ", Y target: " << yTarget + << ", gives gain " << yGain; + if (extra_gain < 1.01) + break; + } + + computeExposure(context, yGain); + frameCount_++; +} + +} /* namespace ipa::rkisp1::algorithms */ + +} /* namespace libcamera */ -- cgit v1.2.1