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ColorStatistics.java
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144 lines (135 loc) · 3.73 KB
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package ij.process;
import ij.measure.Calibration;
/** RGB image statistics, including histogram. */
public class ColorStatistics extends ImageStatistics {
/** Construct an ImageStatistics object from a ColorProcessor
using the standard measurement options (area, mean,
mode, min and max). */
public ColorStatistics(ImageProcessor ip) {
this(ip, AREA+MEAN+MODE+MIN_MAX, null);
}
/** Constructs a ColorStatistics object from a ColorProcessor using
the specified measurement options.
*/
public ColorStatistics(ImageProcessor ip, int mOptions, Calibration cal) {
setup(ip, cal);
if (ip instanceof IntProcessor) {
getIntStatistics(ip);
return;
}
ColorProcessor cp = (ColorProcessor)ip;
histogram = cp.getHistogram();
getRawStatistics(0,255);
if ((mOptions&MIN_MAX)!=0)
getRawMinAndMax(0,255);
if ((mOptions&ELLIPSE)!=0 || (mOptions&SHAPE_DESCRIPTORS)!=0)
fitEllipse(ip, mOptions);
else if ((mOptions&CENTROID)!=0)
getCentroid(ip);
if ((mOptions&(CENTER_OF_MASS|SKEWNESS|KURTOSIS))!=0)
calculateMoments(ip);
if ((mOptions&MEDIAN)!=0)
calculateMedian(histogram, 0, 255, cal);
}
void calculateMoments(ImageProcessor ip) {
byte[] mask = ip.getMaskArray();
int i, mi;
double v, v2, sum1=0.0, sum2=0.0, sum3=0.0, sum4=0.0, xsum=0.0, ysum=0.0;
for (int y=ry,my=0; y<(ry+rh); y++,my++) {
i = y*width + rx;
mi = my*rw;
for (int x=rx; x<(rx+rw); x++) {
if (mask==null || mask[mi++]!=0) {
v = ip.getPixelValue(x, y);
v2 = v*v;
sum1 += v;
sum2 += v2;
sum3 += v*v2;
sum4 += v2*v2;
xsum += x*v;
ysum += y*v;
}
i++;
}
}
double mean2 = mean*mean;
double variance = sum2/pixelCount - mean2;
double sDeviation = Math.sqrt(variance);
skewness = ((sum3 - 3.0*mean*sum2)/pixelCount + 2.0*mean*mean2)/(variance*sDeviation);
kurtosis = (((sum4 - 4.0*mean*sum3 + 6.0*mean2*sum2)/pixelCount - 3.0*mean2*mean2)/(variance*variance)-3.0);
xCenterOfMass = xsum/sum1+0.5;
yCenterOfMass = ysum/sum1+0.5;
if (cal!=null) {
xCenterOfMass = cal.getX(xCenterOfMass);
yCenterOfMass = cal.getY(yCenterOfMass, height);
}
}
void getIntStatistics(ImageProcessor ip) {
int v;
int[] pixels = (int[])ip.getPixels();
nBins = ip.getHistogramSize();
histogram = new int[nBins];
double sum = 0;
double sum2 = 0;
byte[] mask = ip.getMaskArray();
// Find image min and max
int roiMin = Integer.MAX_VALUE;
int roiMax = -Integer.MAX_VALUE;
for (int y=ry, my=0; y<(ry+rh); y++, my++) {
int i = y * width + rx;
int mi = my * rw;
for (int x=rx; x<(rx+rw); x++) {
if (mask==null || mask[mi++]!=0) {
v = pixels[i];
if (v<roiMin)
roiMin = v;
if (v>roiMax)
roiMax = v;
}
i++;
}
}
min = roiMin; max = roiMax;
binSize = (max-min+1)/nBins;
histMin = min;
histMax = max;
// Generate histogram
double scale = nBins/(max-min);
int index;
pixelCount = 0;
for (int y=ry, my=0; y<(ry+rh); y++, my++) {
int i = y * width + rx;
int mi = my * rw;
for (int x=rx; x<(rx+rw); x++) {
if (mask==null || mask[mi++]!=0) {
v = pixels[i];
pixelCount++;
sum += v;
sum2 += v*v;
index = (int)(scale*(v-min));
if (index>=nBins)
index = nBins-1;
histogram[index]++;
}
i++;
}
}
area = pixelCount*pw*ph;
mean = sum/pixelCount;
umean = mean;
calculateStdDev(pixelCount, sum, sum2);
// calculate mode
int count;
maxCount = 0;
for (int i = 0; i < nBins; i++) {
count = histogram[i];
if (count > maxCount) {
maxCount = count;
mode = i;
}
}
dmode = histMin+mode*binSize;
if (binSize!=1.0)
dmode += binSize/2.0;
}
}