[libcamera-devel] [PATCH v3] ipa: raspberrypi: alsc: Limit the calculated lambda values
Naushir Patuck
naush at raspberrypi.com
Wed Apr 6 13:52:25 CEST 2022
Hi Laurent,
On Wed, 6 Apr 2022 at 11:11, Laurent Pinchart <
laurent.pinchart at ideasonboard.com> wrote:
> From: Naushir Patuck <naush at raspberrypi.com>
>
> Under the right circumstances, the alsc calculations could spread the
> colour
> errors across the entire image as lambda remains unbound. This would cause
> the
> corrected image chroma values to slowly drift to incorrect values.
>
> This change adds a config parameter (alsc.lambda_bound) that provides an
> upper
> and lower bound to the lambda value at every stage of the calculation.
> With this
> change, we now adjust the lambda values so that the average across the
> entire
> grid is 1 instead of normalising to the minimum value.
>
> Signed-off-by: Naushir Patuck <naush at raspberrypi.com>
> Reviewed-by: David Plowman <david.plowman at raspberrypi.com>
> Reviewed-by: Laurent Pinchart <laurent.pinchart at ideasonboard.com>
> Signed-off-by: Laurent Pinchart <laurent.pinchart at ideasonboard.com>
> ---
> Changes since v2:
>
> - Fix typo
> - Use Span and std::accumulate
>
> Naush, could you please test this to make sure I haven't messed up
> anything ?
>
Looks good!
Tested-by: Naushir Patuck <naush at raspberrypi.com>
>
> src/ipa/raspberrypi/controller/rpi/alsc.cpp | 58 +++++++++++++++------
> src/ipa/raspberrypi/controller/rpi/alsc.hpp | 1 +
> 2 files changed, 44 insertions(+), 15 deletions(-)
>
> diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.cpp
> b/src/ipa/raspberrypi/controller/rpi/alsc.cpp
> index be3d1ae476cd..e575c14a92db 100644
> --- a/src/ipa/raspberrypi/controller/rpi/alsc.cpp
> +++ b/src/ipa/raspberrypi/controller/rpi/alsc.cpp
> @@ -4,9 +4,12 @@
> *
> * alsc.cpp - ALSC (auto lens shading correction) control algorithm
> */
> +
> #include <math.h>
> +#include <numeric>
>
> #include <libcamera/base/log.h>
> +#include <libcamera/base/span.h>
>
> #include "../awb_status.h"
> #include "alsc.hpp"
> @@ -149,6 +152,7 @@ void Alsc::Read(boost::property_tree::ptree const
> ¶ms)
> read_calibrations(config_.calibrations_Cb, params,
> "calibrations_Cb");
> config_.default_ct = params.get<double>("default_ct", 4500.0);
> config_.threshold = params.get<double>("threshold", 1e-3);
> + config_.lambda_bound = params.get<double>("lambda_bound", 0.05);
> }
>
> static double get_ct(Metadata *metadata, double default_ct);
> @@ -610,30 +614,47 @@ static double compute_lambda_top_end(int i, double
> const M[XY][4],
>
> // Gauss-Seidel iteration with over-relaxation.
> static double gauss_seidel2_SOR(double const M[XY][4], double omega,
> - double lambda[XY])
> + double lambda[XY], double lambda_bound)
> {
> + const double min = 1 - lambda_bound, max = 1 + lambda_bound;
> double old_lambda[XY];
> int i;
> for (i = 0; i < XY; i++)
> old_lambda[i] = lambda[i];
> lambda[0] = compute_lambda_bottom_start(0, M, lambda);
> - for (i = 1; i < X; i++)
> + lambda[0] = std::clamp(lambda[0], min, max);
> + for (i = 1; i < X; i++) {
> lambda[i] = compute_lambda_bottom(i, M, lambda);
> - for (; i < XY - X; i++)
> + lambda[i] = std::clamp(lambda[i], min, max);
> + }
> + for (; i < XY - X; i++) {
> lambda[i] = compute_lambda_interior(i, M, lambda);
> - for (; i < XY - 1; i++)
> + lambda[i] = std::clamp(lambda[i], min, max);
> + }
> + for (; i < XY - 1; i++) {
> lambda[i] = compute_lambda_top(i, M, lambda);
> + lambda[i] = std::clamp(lambda[i], min, max);
> + }
> lambda[i] = compute_lambda_top_end(i, M, lambda);
> + lambda[i] = std::clamp(lambda[i], min, max);
> // Also solve the system from bottom to top, to help spread the
> updates
> // better.
> lambda[i] = compute_lambda_top_end(i, M, lambda);
> - for (i = XY - 2; i >= XY - X; i--)
> + lambda[i] = std::clamp(lambda[i], min, max);
> + for (i = XY - 2; i >= XY - X; i--) {
> lambda[i] = compute_lambda_top(i, M, lambda);
> - for (; i >= X; i--)
> + lambda[i] = std::clamp(lambda[i], min, max);
> + }
> + for (; i >= X; i--) {
> lambda[i] = compute_lambda_interior(i, M, lambda);
> - for (; i >= 1; i--)
> + lambda[i] = std::clamp(lambda[i], min, max);
> + }
> + for (; i >= 1; i--) {
> lambda[i] = compute_lambda_bottom(i, M, lambda);
> + lambda[i] = std::clamp(lambda[i], min, max);
> + }
> lambda[0] = compute_lambda_bottom_start(0, M, lambda);
> + lambda[0] = std::clamp(lambda[0], min, max);
> double max_diff = 0;
> for (i = 0; i < XY; i++) {
> lambda[i] = old_lambda[i] + (lambda[i] - old_lambda[i]) *
> omega;
> @@ -653,15 +674,24 @@ static void normalise(double *ptr, size_t n)
> ptr[i] /= minval;
> }
>
> +// Rescale the values so that the average value is 1.
> +static void reaverage(Span<double> data)
> +{
> + double sum = std::accumulate(data.begin(), data.end(), 0.0);
> + double ratio = 1 / (sum / data.size());
> + for (double &d : data)
> + d *= ratio;
> +}
> +
> static void run_matrix_iterations(double const C[XY], double lambda[XY],
> double const W[XY][4], double omega,
> - int n_iter, double threshold)
> + int n_iter, double threshold, double
> lambda_bound)
> {
> double M[XY][4];
> construct_M(C, W, M);
> double last_max_diff = std::numeric_limits<double>::max();
> for (int i = 0; i < n_iter; i++) {
> - double max_diff = fabs(gauss_seidel2_SOR(M, omega,
> lambda));
> + double max_diff = fabs(gauss_seidel2_SOR(M, omega, lambda,
> lambda_bound));
> if (max_diff < threshold) {
> LOG(RPiAlsc, Debug)
> << "Stop after " << i + 1 << " iterations";
> @@ -675,10 +705,8 @@ static void run_matrix_iterations(double const C[XY],
> double lambda[XY],
> << last_max_diff << " to " << max_diff;
> last_max_diff = max_diff;
> }
> - // We're going to normalise the lambdas so the smallest is 1. Not
> sure
> - // this is really necessary as they get renormalised later, but I
> - // suppose it does stop these quantities from wandering off...
> - normalise(lambda, XY);
> + // We're going to normalise the lambdas so the total average is 1.
> + reaverage({ lambda, XY });
> }
>
> static void add_luminance_rb(double result[XY], double const lambda[XY],
> @@ -737,9 +765,9 @@ void Alsc::doAlsc()
> compute_W(Cb, config_.sigma_Cb, Wb);
> // Run Gauss-Seidel iterations over the resulting matrix, for R
> and B.
> run_matrix_iterations(Cr, lambda_r_, Wr, config_.omega,
> config_.n_iter,
> - config_.threshold);
> + config_.threshold, config_.lambda_bound);
> run_matrix_iterations(Cb, lambda_b_, Wb, config_.omega,
> config_.n_iter,
> - config_.threshold);
> + config_.threshold, config_.lambda_bound);
> // Fold the calibrated gains into our final lambda values. (Note
> that on
> // the next run, we re-start with the lambda values that don't
> have the
> // calibration gains included.)
> diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.hpp
> b/src/ipa/raspberrypi/controller/rpi/alsc.hpp
> index 9616b99ea7ca..d1dbe0d1d22d 100644
> --- a/src/ipa/raspberrypi/controller/rpi/alsc.hpp
> +++ b/src/ipa/raspberrypi/controller/rpi/alsc.hpp
> @@ -41,6 +41,7 @@ struct AlscConfig {
> std::vector<AlscCalibration> calibrations_Cb;
> double default_ct; // colour temperature if no metadata found
> double threshold; // iteration termination threshold
> + double lambda_bound; // upper/lower bound for lambda from a value
> of 1
> };
>
> class Alsc : public Algorithm
> --
> Regards,
>
> Laurent Pinchart
>
>
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