package ij.plugin;
import ij.*;
import ij.process.*;
import ij.gui.*;
import ij.measure.*;
import java.awt.*;
/** Implements ImageJ's Process/Enhance Contrast command. */
public class ContrastEnhancer implements PlugIn, Measurements {
int max, range;
boolean classicEqualization;
int stackSize;
boolean updateSelectionOnly;
boolean equalize, normalize, processStack, useStackHistogram, entireImage;
static double saturated = 0.35;
static boolean gEqualize, gNormalize;
public void run(String arg) {
ImagePlus imp = IJ.getImage();
stackSize = imp.getStackSize();
imp.trimProcessor();
if (!showDialog(imp))
return;
Roi roi = imp.getRoi();
if (roi!=null) roi.endPaste();
if (stackSize==1)
Undo.setup(Undo.TRANSFORM, imp);
else
Undo.reset();
if (equalize)
equalize(imp);
else
stretchHistogram(imp, saturated);
if (equalize || normalize)
imp.getProcessor().resetMinAndMax();
imp.updateAndDraw();
}
boolean showDialog(ImagePlus imp) {
equalize=gEqualize; normalize=gNormalize;
int bitDepth = imp.getBitDepth();
boolean composite = imp.isComposite();
if (composite) stackSize = 1;
Roi roi = imp.getRoi();
boolean areaRoi = roi!=null && roi.isArea() && !composite;
GenericDialog gd = new GenericDialog("Enhance Contrast");
gd.addNumericField("Saturated Pixels:", saturated, 1, 4, "%");
if (bitDepth!=24 && !composite)
gd.addCheckbox("Normalize", normalize);
if (areaRoi) {
String label = bitDepth==24?"Update Entire Image":"Update All When Normalizing";
gd.addCheckbox(label, entireImage);
}
gd.addCheckbox("Equalize Histogram", equalize);
if (stackSize>1) {
if (!composite)
gd.addCheckbox("Normalize_All "+stackSize+" Slices", processStack);
gd.addCheckbox("Use Stack Histogram", useStackHistogram);
}
gd.showDialog();
if (gd.wasCanceled())
return false;
saturated = gd.getNextNumber();
if (bitDepth!=24 && !composite)
normalize = gd.getNextBoolean();
else
normalize = false;
if (areaRoi) {
entireImage = gd.getNextBoolean();
updateSelectionOnly = !entireImage;
if (!normalize && bitDepth!=24)
updateSelectionOnly = false;
}
equalize = gd.getNextBoolean();
processStack = stackSize>1?gd.getNextBoolean():false;
useStackHistogram = stackSize>1?gd.getNextBoolean():false;
if (saturated<0.0) saturated = 0.0;
if (saturated>100.0) saturated = 100;
if (processStack)
normalize = true;
gEqualize=equalize; gNormalize=normalize;
return true;
}
public void stretchHistogram(ImagePlus imp, double saturated) {
ImageStatistics stats = null;
if (useStackHistogram)
stats = new StackStatistics(imp);
if (processStack) {
ImageStack stack = imp.getStack();
for (int i=1; i<=stackSize; i++) {
IJ.showProgress(i, stackSize);
ImageProcessor ip = stack.getProcessor(i);
ip.setRoi(imp.getRoi());
if (!useStackHistogram)
stats = ImageStatistics.getStatistics(ip, MIN_MAX, null);
stretchHistogram(ip, saturated, stats);
}
} else {
ImageProcessor ip = imp.getProcessor();
ip.setRoi(imp.getRoi());
if (stats==null)
stats = ImageStatistics.getStatistics(ip, MIN_MAX, null);
if (imp.isComposite())
stretchCompositeImageHistogram((CompositeImage)imp, saturated, stats);
else
stretchHistogram(ip, saturated, stats);
}
}
public void stretchHistogram(ImageProcessor ip, double saturated) {
useStackHistogram = false;
stretchHistogram(new ImagePlus("", ip), saturated);
}
public void stretchHistogram(ImageProcessor ip, double saturated, ImageStatistics stats) {
int[] a = getMinAndMax(ip, saturated, stats);
int hmin=a[0], hmax=a[1];
//IJ.log(hmin+" "+hmax+" "+threshold);
if (hmax>hmin) {
double min = stats.histMin+hmin*stats.binSize;
double max = stats.histMin+hmax*stats.binSize;
if (stats.histogram16!=null && ip instanceof ShortProcessor) {
min = hmin;
max = hmax;
}
if (!updateSelectionOnly)
ip.resetRoi();
if (normalize)
normalize(ip, min, max);
else {
if (updateSelectionOnly) {
ImageProcessor mask = ip.getMask();
if (mask!=null) ip.snapshot();
ip.setMinAndMax(min, max);
if (mask!=null) ip.reset(mask);
} else
ip.setMinAndMax(min, max);
}
}
}
void stretchCompositeImageHistogram(CompositeImage imp, double saturated, ImageStatistics stats) {
ImageProcessor ip = imp.getProcessor();
int[] a = getMinAndMax(ip, saturated, stats);
int hmin=a[0], hmax=a[1];
if (hmax>hmin) {
double min = stats.histMin+hmin*stats.binSize;
double max = stats.histMin+hmax*stats.binSize;
if (stats.histogram16!=null && imp.getBitDepth()==16) {
min = hmin;
max = hmax;
}
imp.setDisplayRange(min, max);
}
/*
int channels = imp.getNChannels();b
int channel = imp.getChannel();
int slice = imp.getSlice();
int frame = imp.getFrame();
for (int c=1; c<=channels; c++) {
imp.setPosition(c, slice, frame);
ImageProcessor ip = imp.getProcessor();
int[] a = getMinAndMax(ip, saturated, stats);
int hmin=a[0], hmax=a[1];
if (hmax>hmin) {
double min = stats.histMin+hmin*stats.binSize;
double max = stats.histMin+hmax*stats.binSize;
imp.setDisplayRange(min, max);
}
}
imp.setPosition(channel, slice, frame);
*/
}
int[] getMinAndMax(ImageProcessor ip, double saturated, ImageStatistics stats) {
int hmin, hmax;
int threshold;
int[] histogram = stats.histogram;
if (stats.histogram16!=null && ip instanceof ShortProcessor)
histogram = stats.histogram16;
int hsize = histogram.length;
if (saturated>0.0)
threshold = (int)(stats.pixelCount*saturated/200.0);
else
threshold = 0;
int i = -1;
boolean found = false;
int count = 0;
int maxindex = hsize-1;
do {
i++;
count += histogram[i];
found = count>threshold;
} while (!found && i<maxindex);
hmin = i;
i = hsize;
count = 0;
do {
i--;
count += histogram[i];
found = count>threshold;
} while (!found && i>0);
hmax = i;
int[] a = new int[2];
a[0]=hmin; a[1]=hmax;
return a;
}
void normalize(ImageProcessor ip, double min, double max) {
int min2 = 0;
int max2 = 255;
int range = 256;
if (ip instanceof ShortProcessor)
{max2 = 65535; range=65536;}
else if (ip instanceof FloatProcessor)
normalizeFloat(ip, min, max);
//double scale = range/max-min);
int[] lut = new int[range];
for (int i=0; i<range; i++) {
if (i<=min)
lut[i] = 0;
else if (i>=max)
lut[i] = max2;
else
lut[i] = (int)(((double)(i-min)/(max-min))*max2);
}
applyTable(ip, lut);
}
void applyTable(ImageProcessor ip, int[] lut) {
if (updateSelectionOnly) {
ImageProcessor mask = ip.getMask();
if (mask!=null) ip.snapshot();
ip.applyTable(lut);
if (mask!=null) ip.reset(mask);
} else
ip.applyTable(lut);
}
void normalizeFloat(ImageProcessor ip, double min, double max) {
double scale = max>min?1.0/(max-min):1.0;
int size = ip.getWidth()*ip.getHeight();
float[] pixels = (float[])ip.getPixels();
double v;
for (int i=0; i<size; i++) {
v = pixels[i] - min;
if (v<0.0) v = 0.0;
v *= scale;
if (v>1.0) v = 1.0;
pixels[i] = (float)v;
}
}
public void equalize(ImagePlus imp) {
if (imp.getBitDepth()==32) {
IJ.showMessage("Contrast Enhancer", "Equalization of 32-bit images not supported.");
return;
}
classicEqualization = IJ.altKeyDown();
if (processStack) {
//int[] mask = imp.getMask();
//Rectangle rect = imp.get
ImageStack stack = imp.getStack();
for (int i=1; i<=stackSize; i++) {
IJ.showProgress(i, stackSize);
ImageProcessor ip = stack.getProcessor(i);
equalize(ip);
}
} else
equalize(imp.getProcessor());
}
/**
Changes the tone curves of images.
It should bring up the detail in the flat regions of your image.
Histogram Equalization can enhance meaningless detail and hide
important but small high-contrast features. This method uses a
similar algorithm, but uses the square root of the histogram
values, so its effects are less extreme. Hold the alt key down
to use the standard histogram equalization algorithm.
This code was contributed by Richard Kirk (rak@cre.canon.co.uk).
*/
public void equalize(ImageProcessor ip) {
int[] histogram = ip.getHistogram();
ip.resetRoi();
if (ip instanceof ShortProcessor) { // Short
max = 65535;
range = 65535;
} else { //bytes
max = 255;
range = 255;
}
double sum;
sum = getWeightedValue(histogram, 0);
for (int i=1; i<max; i++)
sum += 2 * getWeightedValue(histogram, i);
sum += getWeightedValue(histogram, max);
double scale = range/sum;
int[] lut = new int[range+1];
lut[0] = 0;
sum = getWeightedValue(histogram, 0);
for (int i=1; i<max; i++) {
double delta = getWeightedValue(histogram, i);
sum += delta;
lut[i] = (int)Math.round(sum*scale);
sum += delta;
}
lut[max] = max;
applyTable(ip, lut);
}
private double getWeightedValue(int[] histogram, int i) {
int h = histogram[i];
if (h<2 || classicEqualization) return (double)h;
return Math.sqrt((double)(h));
}
}