image-js
Version:
Image processing and manipulation in JavaScript
82 lines (74 loc) • 2.56 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", {
value: true
});
exports.default = maxEntropy;
/*
* see http://rsb.info.nih.gov/ij/developer/source/ij/process/AutoThresholder.java.html
* The method is present in: Implements Kapur-Sahoo-Wong (Maximum Entropy) thresholding method:
* Kapur, JN; Sahoo, PK & Wong, ACK (1985), "A New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram",
* Graphical Models and Image Processing 29(3): 273-285
* @param histogram - the histogram of the image
* total - the number of pixels in the image
* @returns {number} - the threshold
*/
function maxEntropy(histogram, total) {
let normHisto = new Array(histogram.length); // normalized histogram
for (let ih = 0; ih < histogram.length; ih++) {
normHisto[ih] = histogram[ih] / total;
}
let P1 = new Array(histogram.length); // cumulative normalized histogram
let P2 = new Array(histogram.length);
P1[0] = normHisto[0];
P2[0] = 1.0 - P1[0];
for (let ih = 1; ih < histogram.length; ih++) {
P1[ih] = P1[ih - 1] + normHisto[ih];
P2[ih] = 1.0 - P1[ih];
}
/* Determine the first non-zero bin */
let firstBin = 0;
for (let ih = 0; ih < histogram.length; ih++) {
if (Math.abs(P1[ih]) >= Number.EPSILON) {
firstBin = ih;
break;
}
}
/* Determine the last non-zero bin */
let lastBin = histogram.length - 1;
for (let ih = histogram.length - 1; ih >= firstBin; ih--) {
if (Math.abs(P2[ih]) >= Number.EPSILON) {
lastBin = ih;
break;
}
}
// Calculate the total entropy each gray-level
// and find the threshold that maximizes it
let threshold = -1;
let totEnt; // total entropy
let maxEnt = Number.MIN_VALUE; // max entropy
let entBack; // entropy of the background pixels at a given threshold
let entObj; // entropy of the object pixels at a given threshold
for (let it = firstBin; it <= lastBin; it++) {
/* Entropy of the background pixels */
entBack = 0.0;
for (let ih = 0; ih <= it; ih++) {
if (histogram[ih] !== 0) {
entBack -= normHisto[ih] / P1[it] * Math.log(normHisto[ih] / P1[it]);
}
}
/* Entropy of the object pixels */
entObj = 0.0;
for (let ih = it + 1; ih < histogram.length; ih++) {
if (histogram[ih] !== 0) {
entObj -= normHisto[ih] / P2[it] * Math.log(normHisto[ih] / P2[it]);
}
}
/* Total entropy */
totEnt = entBack + entObj;
if (maxEnt < totEnt) {
maxEnt = totEnt;
threshold = it;
}
}
return threshold;
}