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#include <vector>
#include <iostream>
#include <fstream>
#include <cmath>
#include <HdrCreation/responses.h>
using namespace std;
using namespace libhdr::fusion;
static const size_t SAMPLES = 1024;
static float getSample(int sample)
{
return static_cast<float>(sample)/(SAMPLES - 1);
}
void printResponseCurve(const ResponseCurve& responseFunction1,
void (*responseFunction2)(float*, int) ,
const std::string& fileNameGnuplot,
const std::string& fileNameMatlab)
{
vector<float> data(SAMPLES);
ofstream outputFile(fileNameGnuplot.c_str());
responseFunction2(data.data(), SAMPLES);
for (size_t idx = 0; idx < SAMPLES; ++idx)
{
float sample = getSample(idx);
float w = responseFunction1.getResponse(sample);
outputFile << idx << " "
<< sample << " "
<< data[idx] << " "
<< w << " "
<< abs(data[idx] - w)
<< "\n";
}
outputFile.close();
responseFunction1.writeToFile(fileNameMatlab);
}
void responseLinear( float* I, int M )
{
for (int m=0 ; m<M ; m++)
{
I[m] = m / float(M-1); // range is not important, values are normalized later
}
}
void responseLog10( float* I, int M )
{
const float mid = 0.5f * M;
const float norm = 0.0625f * M;
const float maxValue = powf(10.0f, float(M-1 - mid) / norm);
for (int m=0 ; m < M; ++m)
{
I[m] = powf(10.0f, float(m - mid) / norm) / maxValue;
}
}
void responseGamma( float* I, int M )
{
float norm = M / 4.0f;
// response curve decided empirically
for( int m=0 ; m<M ; m++ )
I[m] = powf( m/norm, 1.7f ) + 1e-4;
}
int main()
{
printResponseCurve(ResponseCurve(RESPONSE_LINEAR), &responseLinear,
"response_linear.dat", "response_linear.m");
printResponseCurve(ResponseCurve(RESPONSE_LOG10), &responseLog10,
"response_log10.dat", "response_log10.m");
printResponseCurve(ResponseCurve(RESPONSE_GAMMA), &responseGamma,
"response_gamma.dat", "response_gamma.m");
printResponseCurve(ResponseCurve(RESPONSE_SRGB), &responseLinear,
"response_srgb.dat", "response_srgb.m");
return 0;
}
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