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ipa: ipu3: agc: Saturate the averages when computing relative luminance

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The relative luminance is calculated using an iterative process to
account for saturation in the sensor, as multiplying pixels by a gain
doesn't increase the relative luminance by the same factor if some
regions are saturated. Relative luminance estimation doesn't apply a
saturation, which produces a value that doesn't match what the sensor
will output, and defeats the point of the iterative process. Fix it.

Fixes: f8f07f9468 ("ipa: ipu3: agc: Improve gain calculation")
Signed-off-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com>
Tested-by: Jean-Michel Hautbois <jeanmichel.hautbois@ideasonboard.com>
Reviewed-by: Jean-Michel Hautbois <jeanmichel.hautbois@ideasonboard.com>
Tested-by: Kieran Bingham <kieran.bingham@ideasonboard.com>
Reviewed-by: Kieran Bingham <kieran.bingham@ideasonboard.com>
This commit is contained in:
Laurent Pinchart 2021-11-16 16:29:23 +02:00
parent a2b4975a1c
commit b0e31c9020
1 changed files with 18 additions and 7 deletions
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25
src/ipa/ipu3/algorithms/agc.cpp
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@ -252,10 +252,19 @@ void Agc::computeExposure(IPAFrameContext &frameContext, double yGain,
* \param[in] gain The gain to apply to the frame
* \return The relative luminance
*
* Luma is the weighted sum of gamma-compressed R′G′B′ components of a color
* video. The luma values are normalized as 0.0 to 1.0, with 1.0 being a
* theoretical perfect reflector of 100% reference white. We use the Rec. 601
* luma here.
* 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 AWB statistics for the current frame. Red,
* green and blue 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.
*
* The relative luminance (Y) is computed from the linear RGB components using
* the Rec. 601 formula. 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
@ -267,6 +276,7 @@ double Agc::estimateLuminance(IPAFrameContext &frameContext,
{
double redSum = 0, greenSum = 0, blueSum = 0;
/* Sum the per-channel averages, saturated to 255. */
for (unsigned int cellY = 0; cellY < grid.height; cellY++) {
for (unsigned int cellX = 0; cellX < grid.width; cellX++) {
uint32_t cellPosition = cellY * stride_ + cellX;
@ -275,10 +285,11 @@ double Agc::estimateLuminance(IPAFrameContext &frameContext,
reinterpret_cast<const ipu3_uapi_awb_set_item *>(
&stats->awb_raw_buffer.meta_data[cellPosition]
);
const uint8_t G_avg = (cell->Gr_avg + cell->Gb_avg) / 2;
redSum += cell->R_avg * gain;
greenSum += (cell->Gr_avg + cell->Gb_avg) / 2 * gain;
blueSum += cell->B_avg * gain;
redSum += std::min(cell->R_avg * gain, 255.0);
greenSum += std::min(G_avg * gain, 255.0);
blueSum += std::min(cell->B_avg * gain, 255.0);
}
}