diff options
Diffstat (limited to 'src')
| -rw-r--r-- | src/ipa/raspberrypi/controller/rpi/alsc.cpp | 58 | ||||
| -rw-r--r-- | 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 be3d1ae4..e575c14a 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 9616b99e..d1dbe0d1 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 |