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ipa: rkisp1: Remove bespoke Agc functions
Now that the rkisp1 Agc algorithm is a derivation of MeanLuminanceAgc we can remove the bespoke functions from the IPA's class. Reviewed-by: Stefan Klug <stefan.klug@ideasonboard.com> Reviewed-by: Paul Elder <paul.elder@ideasonboard.com> Reviewed-by: Jacopo Mondi <jacopo.mondi@ideasonboard.com> Signed-off-by: Daniel Scally <dan.scally@ideasonboard.com> Signed-off-by: Kieran Bingham <kieran.bingham@ideasonboard.com>
This commit is contained in:
Daniel Scally
Kieran Bingham
parent
4c5152843a
commit
fdcd5d04ec
2 changed files with 25 additions and 237 deletions
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@ -36,30 +36,7 @@ namespace ipa::rkisp1::algorithms {
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LOG_DEFINE_CATEGORY(RkISP1Agc)
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/* Minimum limit for analogue gain value */
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static constexpr double kMinAnalogueGain = 1.0;
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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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/* Target value to reach for the top 2% of the histogram */
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static constexpr double kEvGainTarget = 0.5;
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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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supportsRaw_ = true;
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}
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@ -116,12 +93,6 @@ int Agc::configure(IPAContext &context, const IPACameraSensorInfo &configInfo)
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context.configuration.agc.measureWindow.h_size = 3 * configInfo.outputSize.width / 4;
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context.configuration.agc.measureWindow.v_size = 3 * configInfo.outputSize.height / 4;
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/*
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* \todo Use the upcoming per-frame context API that will provide a
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* frame index
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*/
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frameCount_ = 0;
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/* \todo Run this again when FrameDurationLimits is passed in */
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setLimits(context.configuration.sensor.minShutterSpeed,
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context.configuration.sensor.maxShutterSpeed,
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@ -223,170 +194,6 @@ void Agc::prepare(IPAContext &context, const uint32_t frame,
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params->module_en_update |= RKISP1_CIF_ISP_MODULE_HST;
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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] context The shared IPA Context
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* \param[in] frameContext The FrameContext for this frame
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* \param[in] yGain The gain calculated on the current brightness level
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* \param[in] iqMeanGain The gain calculated based on the relative luminance target
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*/
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void Agc::computeExposure(IPAContext &context, IPAFrameContext &frameContext,
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double yGain, double iqMeanGain)
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{
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IPASessionConfiguration &configuration = context.configuration;
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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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/* Use the highest of the two gain estimates. */
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double evGain = std::max(yGain, iqMeanGain);
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utils::Duration minShutterSpeed = configuration.sensor.minShutterSpeed;
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utils::Duration maxShutterSpeed = std::min(configuration.sensor.maxShutterSpeed,
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kMaxShutterSpeed);
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double minAnalogueGain = std::max(configuration.sensor.minAnalogueGain,
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kMinAnalogueGain);
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double maxAnalogueGain = configuration.sensor.maxAnalogueGain;
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/* Consider within 1% of the target as correctly exposed. */
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if (utils::abs_diff(evGain, 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 " << evGain;
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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 * evGain;
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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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}
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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] expMeans The mean luminance values, from the RkISP1 statistics
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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(Span<const uint8_t> expMeans, 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 (uint8_t expMean : expMeans)
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ySum += std::min(expMean * gain, 255.0);
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/* \todo Weight with the AWB gains */
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return ySum / expMeans.size() / 255;
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}
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/**
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* \brief Estimate the mean value of the top 2% of the histogram
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* \param[in] hist The histogram statistics computed by the RkISP1
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* \return The mean value of the top 2% of the histogram
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*/
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double Agc::measureBrightness(Span<const uint32_t> hist) const
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{
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Histogram histogram{ hist };
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/* Estimate the quantile mean of the top 2% of the histogram. */
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return histogram.interQuantileMean(0.98, 1.0);
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}
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void Agc::fillMetadata(IPAContext &context, IPAFrameContext &frameContext,
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ControlList &metadata)
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{
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@ -403,6 +210,29 @@ void Agc::fillMetadata(IPAContext &context, IPAFrameContext &frameContext,
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metadata.set(controls::FrameDuration, frameDuration.get<std::micro>());
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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] 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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* 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(double gain) const
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{
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double ySum = 0.0;
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@ -447,40 +277,7 @@ void Agc::process(IPAContext &context, [[maybe_unused]] const uint32_t frame,
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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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Span<const uint8_t> ae{ params->ae.exp_mean, context.hw->numAeCells };
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Span<const uint32_t> hist{
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params->hist.hist_bins,
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context.hw->numHistogramBins
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};
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double iqMean = measureBrightness(hist);
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double iqMeanGain = kEvGainTarget * hist.size() / iqMean;
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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, frameContext, yGain, iqMeanGain);
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frameCount_++;
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Histogram hist({ params->hist.hist_bins, context.hw->numHistogramBins });
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expMeans_ = { params->ae.exp_mean, context.hw->numAeCells };
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/*
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@ -497,7 +294,7 @@ void Agc::process(IPAContext &context, [[maybe_unused]] const uint32_t frame,
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std::tie(shutterTime, aGain, dGain) =
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calculateNewEv(context.activeState.agc.constraintMode,
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context.activeState.agc.exposureMode,
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Histogram(hist), effectiveExposureValue);
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hist, effectiveExposureValue);
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LOG(RkISP1Agc, Debug)
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<< "Divided up shutter, analogue gain and digital gain are "
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@ -44,19 +44,10 @@ public:
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ControlList &metadata) override;
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private:
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void computeExposure(IPAContext &Context, IPAFrameContext &frameContext,
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double yGain, double iqMeanGain);
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utils::Duration filterExposure(utils::Duration exposureValue);
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double estimateLuminance(Span<const uint8_t> expMeans, double gain);
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double measureBrightness(Span<const uint32_t> hist) const;
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void fillMetadata(IPAContext &context, IPAFrameContext &frameContext,
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ControlList &metadata);
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double estimateLuminance(double gain) const override;
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uint64_t frameCount_;
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utils::Duration filteredExposure_;
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Span<const uint8_t> expMeans_;
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};
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