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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin
2018-12-18 19:07:43 +00:00
parent 2fb409b286 b0a08cced9
commit 7fb70e1701
20 changed files with 397 additions and 73 deletions
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modules/stitching/src/exposure_compensate.cpp
+68 -11
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@@ -41,6 +41,10 @@
//M*/
#include "precomp.hpp"
#ifdef HAVE_EIGEN
#include <Eigen/Core>
#include <Eigen/Dense>
#endif
namespace cv {
namespace detail {
@@ -86,6 +90,7 @@ void GainCompensator::feed(const std::vector<Point> &corners, const std::vector<
const int num_images = static_cast<int>(images.size());
Mat_<int> N(num_images, num_images); N.setTo(0);
Mat_<double> I(num_images, num_images); I.setTo(0);
Mat_<bool> skip(num_images, 1); skip.setTo(true);
//Rect dst_roi = resultRoi(corners, images);
Mat subimg1, subimg2;
@@ -105,7 +110,19 @@ void GainCompensator::feed(const std::vector<Point> &corners, const std::vector<
submask2 = masks[j].first(Rect(roi.tl() - corners[j], roi.br() - corners[j])).getMat(ACCESS_READ);
intersect = (submask1 == masks[i].second) & (submask2 == masks[j].second);
N(i, j) = N(j, i) = std::max(1, countNonZero(intersect));
int intersect_count = countNonZero(intersect);
N(i, j) = N(j, i) = std::max(1, intersect_count);
// Don't compute Isums if subimages do not intersect anyway
if (intersect_count == 0)
continue;
// Don't skip images that intersect with at least one other image
if (i != j)
{
skip(i, 0) = false;
skip(j, 0) = false;
}
double Isum1 = 0, Isum2 = 0;
for (int y = 0; y < roi.height; ++y)
@@ -130,22 +147,62 @@ void GainCompensator::feed(const std::vector<Point> &corners, const std::vector<
{
double alpha = 0.01;
double beta = 100;
int num_eq = num_images - countNonZero(skip);
Mat_<double> A(num_images, num_images); A.setTo(0);
Mat_<double> b(num_images, 1); b.setTo(0);
for (int i = 0; i < num_images; ++i)
Mat_<double> A(num_eq, num_eq); A.setTo(0);
Mat_<double> b(num_eq, 1); b.setTo(0);
for (int i = 0, ki = 0; i < num_images; ++i)
{
for (int j = 0; j < num_images; ++j)
if (skip(i, 0))
continue;
for (int j = 0, kj = 0; j < num_images; ++j)
{
b(i, 0) += beta * N(i, j);
A(i, i) += beta * N(i, j);
if (j == i) continue;
A(i, i) += 2 * alpha * I(i, j) * I(i, j) * N(i, j);
A(i, j) -= 2 * alpha * I(i, j) * I(j, i) * N(i, j);
if (skip(j, 0))
continue;
b(ki, 0) += beta * N(i, j);
A(ki, ki) += beta * N(i, j);
if (j != i)
{
A(ki, ki) += 2 * alpha * I(i, j) * I(i, j) * N(i, j);
A(ki, kj) -= 2 * alpha * I(i, j) * I(j, i) * N(i, j);
}
++kj;
}
++ki;
}
solve(A, b, gains_);
Mat_<double> l_gains;
#ifdef HAVE_EIGEN
Eigen::MatrixXf eigen_A, eigen_b, eigen_x;
cv2eigen(A, eigen_A);
cv2eigen(b, eigen_b);
Eigen::LLT<Eigen::MatrixXf> solver(eigen_A);
#if ENABLE_LOG
if (solver.info() != Eigen::ComputationInfo::Success)
LOGLN("Failed to solve exposure compensation system");
#endif
eigen_x = solver.solve(eigen_b);
Mat_<float> l_gains_float;
eigen2cv(eigen_x, l_gains_float);
l_gains_float.convertTo(l_gains, CV_64FC1);
#else
solve(A, b, l_gains);
#endif
CV_CheckTypeEQ(l_gains.type(), CV_64FC1, "");
gains_.create(num_images, 1);
for (int i = 0, j = 0; i < num_images; ++i)
{
if (skip(i, 0))
gains_.at<double>(i, 0) = 1;
else
gains_.at<double>(i, 0) = l_gains(j++, 0);
}
}
LOGLN("Exposure compensation, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");