Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

Robertson update

Browse Source
pull/1474/head
Fedor Morozov 11 years ago
parent deeaddb0a9
commit c118f3c529
6 changed files with 92 additions and 77 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 6
      modules/photo/include/opencv2/photo.hpp
  2. 14
      modules/photo/src/align.cpp
  3. 74
      modules/photo/src/calibrate.cpp
  4. 35
      modules/photo/src/hdr_common.cpp
  5. 8
      modules/photo/src/merge.cpp
  6. 32
      modules/photo/test/test_hdr.cpp

6
modules/photo/include/opencv2/photo.hpp
Unescape View File

@ -80,6 +80,8 @@ CV_EXPORTS_W void fastNlMeansDenoisingColoredMulti( InputArrayOfArrays srcImgs,
float h = 3, float hColor = 3,
int templateWindowSize = 7, int searchWindowSize = 21);
enum { LDR_SIZE = 256 };
class CV_EXPORTS_W Tonemap : public Algorithm
{
public:
@ -227,9 +229,11 @@ public:
CV_WRAP virtual float getThreshold() const = 0;
CV_WRAP virtual void setThreshold(float threshold) = 0;
CV_WRAP virtual Mat getRadiance() const = 0;
};
CV_EXPORTS_W Ptr<CalibrateRobertson> createCalibrateRobertson(int samples = 50, float lambda = 10.0f);
CV_EXPORTS_W Ptr<CalibrateRobertson> createCalibrateRobertson(int max_iter = 30, float threshold = 0.01f);
class CV_EXPORTS_W ExposureMerge : public Algorithm
{

14
modules/photo/src/align.cpp
Unescape View File

@ -243,14 +243,14 @@ protected:
{
int channels = 0;
Mat hist;
int hist_size = 256;
float range[] = {0, 256} ;
int hist_size = LDR_SIZE;
float range[] = {0, LDR_SIZE} ;
const float* ranges[] = {range};
calcHist(&img, 1, &channels, Mat(), hist, 1, &hist_size, ranges);
float *ptr = hist.ptr<float>();
int median = 0, sum = 0;
int thresh = img.total() / 2;
while(sum < thresh && median < 256) {
while(sum < thresh && median < LDR_SIZE) {
sum += static_cast<int>(ptr[median]);
median++;
}
@ -309,7 +309,7 @@ public:
std::vector<Mat> splitted(channels);
split(images[0], splitted);
for(int i = 0; i < images.size() - 1; i++) {
for(size_t i = 0; i < images.size() - 1; i++) {
std::vector<Mat> next_splitted(channels);
split(images[i + 1], next_splitted);
@ -399,7 +399,7 @@ public:
split(radiance, splitted);
std::vector<Mat> resp_split(channels);
split(response, resp_split);
for(int i = 0; i < images.size() - 1; i++) {
for(size_t i = 0; i < images.size() - 1; i++) {
std::vector<Mat> next_splitted(channels);
LUT(images[i + 1], response, radiance);
@ -430,7 +430,9 @@ public:
virtual void process(InputArrayOfArrays src, OutputArray dst, std::vector<float>& times)
{
process(src, dst, times, linearResponse(3));
Mat response = linearResponse(3);
response.at<Vec3f>(0) = response.at<Vec3f>(1);
process(src, dst, times, response);
}
CV_WRAP virtual int getThreshold() {return thresh;}

74
modules/photo/src/calibrate.cpp
Unescape View File

@ -45,7 +45,6 @@
#include "opencv2/imgproc.hpp"
//#include "opencv2/highgui.hpp"
#include "hdr_common.hpp"
#include <iostream>
namespace cv
{
@ -74,7 +73,7 @@ public:
int channels = images[0].channels();
int CV_32FCC = CV_MAKETYPE(CV_32F, channels);
dst.create(256, 1, CV_32FCC);
dst.create(LDR_SIZE, 1, CV_32FCC);
Mat result = dst.getMat();
std::vector<Point> sample_points;
@ -97,7 +96,7 @@ public:
std::vector<Mat> result_split(channels);
for(int channel = 0; channel < channels; channel++) {
Mat A = Mat::zeros(sample_points.size() * images.size() + 257, 256 + sample_points.size(), CV_32F);
Mat A = Mat::zeros(sample_points.size() * images.size() + LDR_SIZE + 1, LDR_SIZE + sample_points.size(), CV_32F);
Mat B = Mat::zeros(A.rows, 1, CV_32F);
int eq = 0;
@ -107,12 +106,12 @@ public:
int val = images[j].ptr()[3*(sample_points[i].y * images[j].cols + sample_points[j].x) + channel];
A.at<float>(eq, val) = w.at<float>(val);
A.at<float>(eq, 256 + i) = -w.at<float>(val);
A.at<float>(eq, LDR_SIZE + i) = -w.at<float>(val);
B.at<float>(eq, 0) = w.at<float>(val) * log(times[j]);
eq++;
}
}
A.at<float>(eq, 128) = 1;
A.at<float>(eq, LDR_SIZE / 2) = 1;
eq++;
for(int i = 0; i < 254; i++) {
@ -123,7 +122,7 @@ public:
}
Mat solution;
solve(A, B, solution, DECOMP_SVD);
solution.rowRange(0, 256).copyTo(result_split[channel]);
solution.rowRange(0, LDR_SIZE).copyTo(result_split[channel]);
}
merge(result_split, result);
exp(result, result);
@ -192,20 +191,14 @@ public:
int channels = images[0].channels();
int CV_32FCC = CV_MAKETYPE(CV_32F, channels);
dst.create(256, 1, CV_32FCC);
dst.create(LDR_SIZE, 1, CV_32FCC);
Mat response = dst.getMat();
response = Mat::zeros(256, 1, CV_32FCC);
for(int i = 0; i < 256; i++) {
for(int c = 0; c < channels; c++) {
response.at<Vec3f>(i)[c] = i / 128.0;
}
}
response = linearResponse(3) / (LDR_SIZE / 2.0f);
Mat card = Mat::zeros(256, 1, CV_32FCC);
for(int i = 0; i < images.size(); i++) {
Mat card = Mat::zeros(LDR_SIZE, 1, CV_32FCC);
for(size_t i = 0; i < images.size(); i++) {
uchar *ptr = images[i].ptr();
for(int pos = 0; pos < images[i].total(); pos++) {
for(size_t pos = 0; pos < images[i].total(); pos++) {
for(int c = 0; c < channels; c++, ptr++) {
card.at<Vec3f>(*ptr)[c] += 1;
}
@ -213,43 +206,34 @@ public:
}
card = 1.0 / card;
Ptr<MergeRobertson> merge = createMergeRobertson();
for(int iter = 0; iter < max_iter; iter++) {
Scalar channel_err(0, 0, 0);
Mat radiance = Mat::zeros(images[0].size(), CV_32FCC);
Mat wsum = Mat::zeros(images[0].size(), CV_32FCC);
for(int i = 0; i < images.size(); i++) {
Mat im, w;
LUT(images[i], weight, w);
LUT(images[i], response, im);
Mat err_mat;
pow(im - times[i] * radiance, 2.0f, err_mat);
err_mat = w.mul(err_mat);
channel_err += sum(err_mat);
radiance += times[i] * w.mul(im);
wsum += pow(times[i], 2) * w;
}
float err = (channel_err[0] + channel_err[1] + channel_err[2]) / (channels * radiance.total());
radiance = radiance.mul(1 / wsum);
radiance = Mat::zeros(images[0].size(), CV_32FCC);
merge->process(images, radiance, times, response);
float* rad_ptr = radiance.ptr<float>();
response = Mat::zeros(256, 1, CV_32FC3);
for(int i = 0; i < images.size(); i++) {
Mat new_response = Mat::zeros(LDR_SIZE, 1, CV_32FC3);
for(size_t i = 0; i < images.size(); i++) {
uchar *ptr = images[i].ptr();
for(int pos = 0; pos < images[i].total(); pos++) {
float* rad_ptr = radiance.ptr<float>();
for(size_t pos = 0; pos < images[i].total(); pos++) {
for(int c = 0; c < channels; c++, ptr++, rad_ptr++) {
response.at<Vec3f>(*ptr)[c] += times[i] * *rad_ptr;
new_response.at<Vec3f>(*ptr)[c] += times[i] * *rad_ptr;
}
}
}
response = response.mul(card);
new_response = new_response.mul(card);
for(int c = 0; c < 3; c++) {
for(int i = 0; i < 256; i++) {
response.at<Vec3f>(i)[c] /= response.at<Vec3f>(128)[c];
float middle = new_response.at<Vec3f>(LDR_SIZE / 2)[c];
for(int i = 0; i < LDR_SIZE; i++) {
new_response.at<Vec3f>(i)[c] /= middle;
}
}
float diff = sum(sum(abs(new_response - response)))[0] / channels;
new_response.copyTo(response);
if(diff < threshold) {
break;
}
}
}
@ -259,6 +243,8 @@ public:
float getThreshold() const { return threshold; }
void setThreshold(float val) { threshold = val; }
Mat getRadiance() const { return radiance; }
void write(FileStorage& fs) const
{
fs << "name" << name
@ -278,7 +264,7 @@ protected:
String name;
int max_iter;
float threshold;
Mat weight;
Mat weight, radiance;
};
Ptr<CalibrateRobertson> createCalibrateRobertson(int max_iter, float threshold)

35
modules/photo/src/hdr_common.cpp
Unescape View File

@ -61,21 +61,22 @@ void checkImageDimensions(const std::vector<Mat>& images)
Mat tringleWeights()
{
Mat w(256, 1, CV_32F);
for(int i = 0; i < 256; i++) {
w.at<float>(i) = i < 128 ? i + 1.0f : 256.0f - i;
Mat w(LDR_SIZE, 1, CV_32F);
int half = LDR_SIZE / 2;
for(int i = 0; i < LDR_SIZE; i++) {
w.at<float>(i) = i < half ? i + 1.0f : LDR_SIZE - i;
}
return w;
}
Mat RobertsonWeights()
{
Mat weight(256, 1, CV_32FC3);
for(int i = 0; i < 256; i++) {
float value = exp(-4.0f * pow(i - 127.5f, 2.0f) / pow(127.5f, 2.0f));
for(int c = 0; c < 3; c++) {
weight.at<Vec3f>(i)[c] = value;
}
Mat weight(LDR_SIZE, 1, CV_32FC3);
float q = (LDR_SIZE - 1) / 4.0f;
for(int i = 0; i < LDR_SIZE; i++) {
float value = i / q - 2.0f;
value = exp(-value * value);
weight.at<Vec3f>(i) = Vec3f::all(value);
}
return weight;
}
@ -94,19 +95,11 @@ void mapLuminance(Mat src, Mat dst, Mat lum, Mat new_lum, float saturation)
Mat linearResponse(int channels)
{
Mat single_response = Mat(256, 1, CV_32F);
for(int i = 1; i < 256; i++) {
single_response.at<float>(i) = static_cast<float>(i);
Mat response = Mat(LDR_SIZE, 1, CV_MAKETYPE(CV_32F, channels));
for(int i = 0; i < LDR_SIZE; i++) {
response.at<Vec3f>(i) = Vec3f::all(i);
}
single_response.at<float>(0) = static_cast<float>(1);
std::vector<Mat> splitted(channels);
for(int c = 0; c < channels; c++) {
splitted[c] = single_response;
}
Mat result;
merge(splitted, result);
return result;
return response;
}
};

8
modules/photo/src/merge.cpp
Unescape View File

@ -43,7 +43,6 @@
#include "opencv2/photo.hpp"
#include "opencv2/imgproc.hpp"
#include "hdr_common.hpp"
#include <iostream>
namespace cv
{
@ -77,9 +76,10 @@ public:
if(response.empty()) {
response = linearResponse(channels);
response.at<Vec3f>(0) = response.at<Vec3f>(1);
}
log(response, response);
CV_Assert(response.rows == 256 && response.cols == 1 &&
CV_Assert(response.rows == LDR_SIZE && response.cols == 1 &&
response.channels() == channels);
Mat exp_values(times);
@ -312,9 +312,9 @@ public:
Mat response = input_response.getMat();
if(response.empty()) {
response = linearResponse(channels) / 128.0f;
response = linearResponse(channels) / (LDR_SIZE / 2.0f);
}
CV_Assert(response.rows == 256 && response.cols == 1 &&
CV_Assert(response.rows == LDR_SIZE && response.cols == 1 &&
response.channels() == channels);
result = Mat::zeros(images[0].size(), CV_32FCC);

32
modules/photo/test/test_hdr.cpp
Unescape View File

@ -187,7 +187,22 @@ TEST(Photo_MergeDebevec, regression)
Mat result, expected;
loadImage(test_path + "merge/debevec.exr", expected);
merge->process(images, result, times, response);
imwrite("test.exr", result);
checkEqual(expected, result, 1e-2f);
}
TEST(Photo_MergeRobertson, regression)
{
string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
vector<Mat> images;
vector<float> times;
loadExposureSeq(test_path + "exposures/", images, times);
Ptr<MergeRobertson> merge = createMergeRobertson();
Mat result, expected;
loadImage(test_path + "merge/robertson.exr", expected);
merge->process(images, result, times);
checkEqual(expected, result, 1e-2f);
}
@ -208,3 +223,18 @@ TEST(Photo_CalibrateDebevec, regression)
minMaxLoc(diff, NULL, &max);
ASSERT_FALSE(max > 0.1);
}
TEST(Photo_CalibrateRobertson, regression)
{
string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/";
vector<Mat> images;
vector<float> times;
Mat response, expected;
loadExposureSeq(test_path + "exposures/", images, times);
loadResponseCSV(test_path + "calibrate/robertson.csv", expected);
Ptr<CalibrateRobertson> calibrate = createCalibrateRobertson();
calibrate->process(images, response, times);
checkEqual(expected, response, 1e-3f);
}
Write Preview
Loading…
Cancel
Save