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 2024-05-02 14:30:46 +01:00 committed by Kieran Bingham
parent 4c5152843a
commit fdcd5d04ec
2 changed files with 25 additions and 237 deletions

View file

@ -36,30 +36,7 @@ namespace ipa::rkisp1::algorithms {
LOG_DEFINE_CATEGORY(RkISP1Agc) LOG_DEFINE_CATEGORY(RkISP1Agc)
/* Minimum limit for analogue gain value */
static constexpr double kMinAnalogueGain = 1.0;
/* \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;
/* Target value to reach for the top 2% of the histogram */
static constexpr double kEvGainTarget = 0.5;
/*
* 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() Agc::Agc()
: frameCount_(0), filteredExposure_(0s)
{ {
supportsRaw_ = true; supportsRaw_ = true;
} }
@ -116,12 +93,6 @@ int Agc::configure(IPAContext &context, const IPACameraSensorInfo &configInfo)
context.configuration.agc.measureWindow.h_size = 3 * configInfo.outputSize.width / 4; context.configuration.agc.measureWindow.h_size = 3 * configInfo.outputSize.width / 4;
context.configuration.agc.measureWindow.v_size = 3 * configInfo.outputSize.height / 4; context.configuration.agc.measureWindow.v_size = 3 * configInfo.outputSize.height / 4;
/*
* \todo Use the upcoming per-frame context API that will provide a
* frame index
*/
frameCount_ = 0;
/* \todo Run this again when FrameDurationLimits is passed in */ /* \todo Run this again when FrameDurationLimits is passed in */
setLimits(context.configuration.sensor.minShutterSpeed, setLimits(context.configuration.sensor.minShutterSpeed,
context.configuration.sensor.maxShutterSpeed, context.configuration.sensor.maxShutterSpeed,
@ -223,170 +194,6 @@ void Agc::prepare(IPAContext &context, const uint32_t frame,
params->module_en_update |= RKISP1_CIF_ISP_MODULE_HST; params->module_en_update |= RKISP1_CIF_ISP_MODULE_HST;
} }
/**
* \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] context The shared IPA Context
* \param[in] frameContext The FrameContext for this frame
* \param[in] yGain The gain calculated on the current brightness level
* \param[in] iqMeanGain The gain calculated based on the relative luminance target
*/
void Agc::computeExposure(IPAContext &context, IPAFrameContext &frameContext,
double yGain, double iqMeanGain)
{
IPASessionConfiguration &configuration = context.configuration;
/* Get the effective exposure and gain applied on the sensor. */
uint32_t exposure = frameContext.sensor.exposure;
double analogueGain = frameContext.sensor.gain;
/* Use the highest of the two gain estimates. */
double evGain = std::max(yGain, iqMeanGain);
utils::Duration minShutterSpeed = configuration.sensor.minShutterSpeed;
utils::Duration maxShutterSpeed = std::min(configuration.sensor.maxShutterSpeed,
kMaxShutterSpeed);
double minAnalogueGain = std::max(configuration.sensor.minAnalogueGain,
kMinAnalogueGain);
double maxAnalogueGain = configuration.sensor.maxAnalogueGain;
/* Consider within 1% of the target as correctly exposed. */
if (utils::abs_diff(evGain, 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 " << evGain;
/*
* Calculate the current exposure value for the scene as the latest
* exposure value applied multiplied by the new estimated gain.
*/
utils::Duration exposureValue = effectiveExposureValue * evGain;
/* 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<utils::Duration>(exposureValue / minAnalogueGain,
minShutterSpeed, maxShutterSpeed);
double stepGain = std::clamp(exposureValue / shutterTime,
minAnalogueGain, maxAnalogueGain);
LOG(RkISP1Agc, Debug) << "Divided up shutter and gain are "
<< shutterTime << " and "
<< stepGain;
}
/**
* \brief Estimate the relative luminance of the frame with a given gain
* \param[in] expMeans The mean luminance values, from the RkISP1 statistics
* \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(Span<const uint8_t> expMeans, double gain)
{
double ySum = 0.0;
/* Sum the averages, saturated to 255. */
for (uint8_t expMean : expMeans)
ySum += std::min(expMean * gain, 255.0);
/* \todo Weight with the AWB gains */
return ySum / expMeans.size() / 255;
}
/**
* \brief Estimate the mean value of the top 2% of the histogram
* \param[in] hist The histogram statistics computed by the RkISP1
* \return The mean value of the top 2% of the histogram
*/
double Agc::measureBrightness(Span<const uint32_t> hist) const
{
Histogram histogram{ hist };
/* Estimate the quantile mean of the top 2% of the histogram. */
return histogram.interQuantileMean(0.98, 1.0);
}
void Agc::fillMetadata(IPAContext &context, IPAFrameContext &frameContext, void Agc::fillMetadata(IPAContext &context, IPAFrameContext &frameContext,
ControlList &metadata) ControlList &metadata)
{ {
@ -403,6 +210,29 @@ void Agc::fillMetadata(IPAContext &context, IPAFrameContext &frameContext,
metadata.set(controls::FrameDuration, frameDuration.get<std::micro>()); metadata.set(controls::FrameDuration, frameDuration.get<std::micro>());
} }
/**
* \brief Estimate the relative luminance of the frame with a given gain
* \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.
*
* 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(double gain) const double Agc::estimateLuminance(double gain) const
{ {
double ySum = 0.0; double ySum = 0.0;
@ -447,40 +277,7 @@ void Agc::process(IPAContext &context, [[maybe_unused]] const uint32_t frame,
const rkisp1_cif_isp_stat *params = &stats->params; const rkisp1_cif_isp_stat *params = &stats->params;
ASSERT(stats->meas_type & RKISP1_CIF_ISP_STAT_AUTOEXP); ASSERT(stats->meas_type & RKISP1_CIF_ISP_STAT_AUTOEXP);
Span<const uint8_t> ae{ params->ae.exp_mean, context.hw->numAeCells }; Histogram hist({ params->hist.hist_bins, context.hw->numHistogramBins });
Span<const uint32_t> hist{
params->hist.hist_bins,
context.hw->numHistogramBins
};
double iqMean = measureBrightness(hist);
double iqMeanGain = kEvGainTarget * hist.size() / iqMean;
/*
* 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, frameContext, yGain, iqMeanGain);
frameCount_++;
expMeans_ = { params->ae.exp_mean, context.hw->numAeCells }; expMeans_ = { params->ae.exp_mean, context.hw->numAeCells };
/* /*
@ -497,7 +294,7 @@ void Agc::process(IPAContext &context, [[maybe_unused]] const uint32_t frame,
std::tie(shutterTime, aGain, dGain) = std::tie(shutterTime, aGain, dGain) =
calculateNewEv(context.activeState.agc.constraintMode, calculateNewEv(context.activeState.agc.constraintMode,
context.activeState.agc.exposureMode, context.activeState.agc.exposureMode,
Histogram(hist), effectiveExposureValue); hist, effectiveExposureValue);
LOG(RkISP1Agc, Debug) LOG(RkISP1Agc, Debug)
<< "Divided up shutter, analogue gain and digital gain are " << "Divided up shutter, analogue gain and digital gain are "

View file

@ -44,19 +44,10 @@ public:
ControlList &metadata) override; ControlList &metadata) override;
private: private:
void computeExposure(IPAContext &Context, IPAFrameContext &frameContext,
double yGain, double iqMeanGain);
utils::Duration filterExposure(utils::Duration exposureValue);
double estimateLuminance(Span<const uint8_t> expMeans, double gain);
double measureBrightness(Span<const uint32_t> hist) const;
void fillMetadata(IPAContext &context, IPAFrameContext &frameContext, void fillMetadata(IPAContext &context, IPAFrameContext &frameContext,
ControlList &metadata); ControlList &metadata);
double estimateLuminance(double gain) const override; double estimateLuminance(double gain) const override;
uint64_t frameCount_;
utils::Duration filteredExposure_;
Span<const uint8_t> expMeans_; Span<const uint8_t> expMeans_;
}; };