Java -> C++
Code
int MaxEntropy(float* histo, int n_length) {
// Implements Kapur-Sahoo-Wong (Maximum Entropy) thresholding method
// Kapur J.N., Sahoo P.K., and Wong A.K.C. (1985) "A New Method for
// Gray-Level Picture Thresholding Using the Entropy of the Histogram"
// Graphical Models and Image Processing, 29(3): 273-285
// M. Emre Celebi
// 06.15.2007
// Ported to ImageJ plugin by G.Landini from E Celebi's fourier_0.8 routines
int threshold = -1;
int ih, it;
int first_bin;
int last_bin;
double tot_ent; /* total entropy */
double max_ent; /* max entropy */
double ent_back; /* entropy of the background pixels at a given threshold */
double ent_obj; /* entropy of the object pixels at a given threshold */
int total = 0;
double* norm_histo = nullptr; /* normalized histogram */
double* P1 = nullptr; /* cumulative normalized histogram */
double* P2 = nullptr;
norm_histo = new double[n_length];
P1 = new double[n_length];
P2 = new double[n_length];
for (ih = 0; ih < n_length; ih++)
total += histo[ih];
for (ih = 0; ih < n_length; ih++)
norm_histo[ih] = (double)histo[ih] / total;
P1[0] = norm_histo[0];
P2[0] = 1.0 - P1[0];
for (ih = 1; ih < n_length; ih++)
{
P1[ih] = P1[ih - 1] + norm_histo[ih];
P2[ih] = 1.0 - P1[ih];
}
/* Determine the first non-zero bin */
first_bin = 0;
for (ih = 0; ih < n_length; ih++)
{
if (!(abs(P1[ih]) < 2.220446049250313E-16))
{
first_bin = ih;
break;
}
}
/* Determine the last non-zero bin */
last_bin = n_length - 1;
for (ih = n_length - 1; ih >= first_bin; ih--)
{
if (!(abs(P2[ih]) < 2.220446049250313E-16))
{
last_bin = ih;
break;
}
}
// Calculate the total entropy each gray-level
// and find the threshold that maximizes it
max_ent = -DBL_MAX;
for (it = first_bin; it <= last_bin; it++)
{
/* Entropy of the background pixels */
ent_back = 0.0;
for (ih = 0; ih <= it; ih++)
{
if (histo[ih] != 0)
{
ent_back -= (norm_histo[ih] / P1[it]) * log(norm_histo[ih] / P1[it]);
}
}
/* Entropy of the object pixels */
ent_obj = 0.0;
for (ih = it + 1; ih < n_length; ih++)
{
if (histo[ih] != 0)
{
ent_obj -= (norm_histo[ih] / P2[it]) * log(norm_histo[ih] / P2[it]);
}
}
/* Total entropy */
tot_ent = ent_back + ent_obj;
// IJ.log(""+max_ent+" "+tot_ent);
if (max_ent < tot_ent)
{
max_ent = tot_ent;
threshold = it;
}
}
if (norm_histo)
delete[] norm_histo;
if (P1)
delete[] P1;
if (P2)
delete[] P2;
return threshold;
}
imageJ 관련 문서 : https://imagej.net/plugins/auto-threshold
github link : https://github.com/fiji/Auto_Threshold/blob/master/src/main/java/fiji/threshold/Auto_Threshold.java
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