double aniComputeFilterCoefficients( double* pFilterX, double* pFilterTanp,
double sigmav, double sigmau, double phi )
{
double sigmax, sigmay, tanp;
double su2, sv2;
double phirad;
double a11, a21, a22;
su2 = sigmau * sigmau;
sv2 = sigmav * sigmav;
phirad = phi;
a11 = cos(phirad) * cos(phirad) * su2 + sin(phirad) * sin(phirad) * sv2;
a21 = cos(phirad) * sin(phirad) * ( su2 - sv2 );
a22 = cos(phirad) * cos(phirad) * sv2 + sin(phirad) * sin(phirad) * su2;
sigmax = sqrt( a11 - a21 * a21 / a22 );
tanp = a21 / a22;
sigmay = sqrt(a22);
/* calculate filter coefficients of x-direction*/
YvVfilterCoef(sigmax, pFilterX);
/* calculate filter coefficients in tanp-direction */
YvVfilterCoef(sigmay, pFilterTanp);
return tanp;
}
void iir_gaussianFilter1D(std::vector<float>& curve, int smoothingKernelSize)
{
if (curve.size() < 3) {
return;
}
double sigma = 5.;
if (smoothingKernelSize > 1) {
sigma *= smoothingKernelSize;
}
double filter[7];
// calculate filter coefficients
YvVfilterCoef(sigma, filter);
// filter
iir_1d_filter(curve.begin(), curve.begin(), curve.size(), filter);
}
static void
computeHistogramStatic(const HistogramRequest & request,
boost::shared_ptr<FinishedHistogram> ret,
int histogramIndex)
{
const int upscale = 5;
std::vector<float> *histo = 0;
switch (histogramIndex) {
case 1:
histo = &ret->histogram1;
break;
case 2:
histo = &ret->histogram2;
break;
case 3:
histo = &ret->histogram3;
break;
default:
break;
}
assert(histo);
/// keep the mode parameter in sync with Histogram::DisplayMode
int mode = request.mode;
///if the mode is RGB, adjust the mode to either R,G or B depending on the histogram index
if (mode == 0) {
mode = histogramIndex + 2;
}
ret->pixelsCount = request.rect.area();
// a histogram with upscale more bins
std::vector<float> histo_upscaled;
switch (mode) {
case 1: //< A
computeHisto<&pix_alpha::val>(request, upscale, &histo_upscaled);
break;
case 2: //<Y
computeHisto<&pix_lum::val>(request, upscale, &histo_upscaled);
break;
case 3: //< R
computeHisto<&pix_red::val>(request, upscale, &histo_upscaled);
break;
case 4: //< G
computeHisto<&pix_green::val>(request, upscale, &histo_upscaled);
break;
case 5: //< B
computeHisto<&pix_blue::val>(request, upscale, &histo_upscaled);
break;
default:
assert(false);
break;
}
double sigma = upscale;
if (request.smoothingKernelSize > 1) {
sigma *= request.smoothingKernelSize;
}
// smooth the upscaled histogram
double filter[7];
/* calculate filter coefficients */
YvVfilterCoef(sigma, filter);
// filter
iir_1d_filter(histo_upscaled.begin(), histo_upscaled.begin(), histo_upscaled.size(), filter);
// downsample to obtain the final histogram
histo->resize(request.binsCount);
assert(histo_upscaled.size() == histo->size() * upscale);
std::vector<float>::const_iterator it_in = histo_upscaled.begin();
std::advance(it_in, (upscale - 1) / 2);
std::vector<float>::iterator it_out = histo->begin();
while ( it_out != histo->end() ) {
*it_out = *it_in * upscale;
++it_out;
if ( it_out != histo->end() ) {
std::advance (it_in,upscale);
}
}
} // computeHistogramStatic
