@@ -17,6 +17,7 @@
#include <libcamera/ipa/core_ipa_interface.h>
+#include "libipa/helpers.h"
#include "libipa/histogram.h"
/**
@@ -185,9 +186,9 @@ double Agc::estimateLuminance(double gain) const
blueSum += std::min(std::get<2>(rgbTriples_[i]) * gain, 255.0);
}
- double ySum = redSum * rGain_ * 0.299
- + greenSum * gGain_ * 0.587
- + blueSum * bGain_ * 0.114;
+ double ySum = ipa::rec601LuminanceFromRGB(redSum * rGain_,
+ greenSum * gGain_,
+ blueSum * bGain_);
return ySum / (bdsGrid_.height * bdsGrid_.width) / 255;
}
@@ -13,6 +13,8 @@
#include <libcamera/control_ids.h>
+#include "libipa/helpers.h"
+
/**
* \file awb.h
*/
@@ -301,36 +303,6 @@ void Awb::prepare(IPAContext &context,
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()
{
@@ -437,7 +409,7 @@ void Awb::awbGreyWorld()
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);
+ asyncResults_.temperatureK = ipa::estimateCCT(sumRed.R, sumRed.G, sumBlue.B);
/*
* Gain values are unsigned integer value ranging [0, 8) with 13 bit
@@ -75,7 +75,6 @@ private:
void generateAwbStats(const ipu3_uapi_stats_3a *stats);
void clearAwbStats();
void awbGreyWorld();
- uint32_t estimateCCT(double red, double green, double blue);
static constexpr uint16_t threshold(float value);
static constexpr uint16_t gainValue(double gain);
Use the centralised libipa helpers instead of open coding common functions. Signed-off-by: Daniel Scally <dan.scally@ideasonboard.com> --- src/ipa/ipu3/algorithms/agc.cpp | 7 ++++--- src/ipa/ipu3/algorithms/awb.cpp | 34 +++------------------------------ src/ipa/ipu3/algorithms/awb.h | 1 - 3 files changed, 7 insertions(+), 35 deletions(-)