public void run(String arg) {
int[] wList = WindowManager.getIDList();
if (wList == null) {
IJ.error("No images are open.");
return;
}
double thalf = 0.5;
boolean keep;
GenericDialog gd = new GenericDialog("Bleach correction");
gd.addNumericField("t½:", thalf, 1);
gd.addCheckbox("Keep source stack:", true);
gd.showDialog();
if (gd.wasCanceled()) return;
long start = System.currentTimeMillis();
thalf = gd.getNextNumber();
keep = gd.getNextBoolean();
if (keep) IJ.run("Duplicate...", "title='Bleach corrected' duplicate");
ImagePlus imp1 = WindowManager.getCurrentImage();
int d1 = imp1.getStackSize();
double v1, v2;
int width = imp1.getWidth();
int height = imp1.getHeight();
ImageProcessor ip1, ip2, ip3;
int slices = imp1.getStackSize();
ImageStack stack1 = imp1.getStack();
ImageStack stack2 = imp1.getStack();
int currentSlice = imp1.getCurrentSlice();
for (int n = 1; n <= slices; n++) {
ip1 = stack1.getProcessor(n);
ip3 = stack1.getProcessor(1);
ip2 = stack2.getProcessor(n);
for (int x = 0; x < width; x++) {
for (int y = 0; y < height; y++) {
v1 = ip1.getPixelValue(x, y);
v2 = ip3.getPixelValue(x, y);
// =B8/(EXP(-C$7*A8))
v1 = (v1 / Math.exp(-n * thalf));
ip2.putPixelValue(x, y, v1);
}
}
IJ.showProgress((double) n / slices);
IJ.showStatus(n + "/" + slices);
}
// stack2.show();
imp1.updateAndDraw();
}
public void run(String arg) {
int[] wList = WindowManager.getIDList();
if (wList==null) {
IJ.error("No images are open.");
return;
}
double kernel=3;
double kernelsum = 0;
double kernelvarsum =0;
double kernalvar = 0;
double sigmawidth = 2;
int kernelindex, minpixnumber;
String[] kernelsize = { "3�,"5�, "7�, "9�};
GenericDialog gd = new GenericDialog("Sigma Filter");
gd.addChoice("Kernel size", kernelsize, kernelsize[0]);
gd.addNumericField("Sigma width",sigmawidth , 2);
gd.addNumericField("Minimum number of pixels", 1, 0);
gd.addCheckbox("Keep source:",true);
gd.addCheckbox("Do all stack:",true);
gd.addCheckbox("Modified Lee's FIlter:",true);
gd.showDialog();
if (gd.wasCanceled()) return ;
kernelindex = gd.getNextChoiceIndex();
sigmawidth = gd.getNextNumber();
minpixnumber = ((int)gd.getNextNumber());
boolean keep = gd.getNextBoolean();
boolean doallstack = gd.getNextBoolean();
boolean modified = gd.getNextBoolean();
if (kernelindex==0) kernel = 3;
if (kernelindex==1) kernel = 5;
if (kernelindex==2) kernel = 7;
if (kernelindex==3) kernel = 9;
long start = System.currentTimeMillis();
if (minpixnumber> (kernel*kernel)){
IJ.showMessage("Sigma filter", "There must be more pixels in the kernel than+\n" + "the minimum number to be included");
return;
}
double v, midintensity;
int x, y, ix, iy;
double sum = 0;
double backupsum =0;
int count = 0;
int n = 0;
if (keep) {IJ.run("Select All"); IJ.run("Duplicate...", "title='Sigma filtered' duplicate");}
int radius = (int)(kernel-1)/2;
ImagePlus imp = WindowManager.getCurrentImage();
ImageStack stack1 = imp.getStack();
int width = imp.getWidth();
int height = imp.getHeight();
int nslices = stack1.getSize();
int cslice = imp.getCurrentSlice();
double status = width*height*nslices;
ImageProcessor ip = imp.getProcessor();
int sstart = 1;
if (!doallstack) {sstart = cslice; nslices=sstart;status = status/nslices;};
for (int i=sstart; i<=nslices; i++) {
imp.setSlice(i);
for (x=radius;x<width+radius;x++) {
for (y=radius;y<height+radius;y++) {
midintensity = ip.getPixelValue(x,y);
count = 0;
sum = 0;
kernelsum =0;
kernalvar =0;
kernelvarsum =0;
backupsum = 0;
//calculate mean of kernel value
for (ix=0;ix<kernel;ix++) {
for (iy=0;iy<kernel;iy++) {
v = ip.getPixelValue(x+ix-radius,y+iy-radius);
kernelsum = kernelsum+v;
}
}
double sigmacalcmean = (kernelsum/(kernel*kernel));
//calculate variance of kernel
for (ix=0;ix<kernel;ix++) {
for (iy=0;iy<kernel;iy++) {
v = ip.getPixelValue(x+ix-radius,y+iy-radius);
kernalvar = (v-sigmacalcmean)*(v-sigmacalcmean);
kernelvarsum = kernelvarsum + kernalvar;
}
}
//double variance = kernelvarsum/kernel;
double sigmacalcvar = kernelvarsum/((kernel*kernel)-1);
//calcuate sigma range = sqrt(variance/(mean^2)) � sigmawidth
double sigmarange = sigmawidth*(Math.sqrt((sigmacalcvar) /(sigmacalcmean*sigmacalcmean)));
//calulate sigma top value and bottom value
double sigmatop = midintensity*(1+sigmarange);
double sigmabottom = midintensity*(1-sigmarange);
//calculate mean of values that differ are in sigma range.
for (ix=0;ix<kernel;ix++) {
for (iy=0;iy<kernel;iy++) {
v = ip.getPixelValue(x+ix-radius,y+iy-radius);
if ((v>=sigmabottom)&&(v<=sigmatop)){
sum = sum+v;
count = count+1; }
backupsum = v+ backupsum;
}
}
//if there are too few pixels in the kernal that are within sigma range, the
//mean of the entire kernal is taken. My modification of Lee's filter is to exclude the central value
//from the calculation of the mean as I assume it to be spuriously high or low
if (!(count>(minpixnumber)))
{sum = (backupsum-midintensity);
count = (int)((kernel*kernel)-1);
if (!modified)
{sum = (backupsum);
count = (int)(kernel*kernel);}
}
double val = (sum/count);
ip.putPixelValue(x,y, val);
n = n+1;
double percentage = (((double)n/status)*100);
IJ.showStatus(IJ.d2s(percentage,0) +"% done");
}
// IJ.showProgress(i, status);
}}
imp.updateAndDraw();
IJ.showStatus(IJ.d2s((System.currentTimeMillis()-start)/1000.0, 2)+" seconds"); }
ImageProcessor setup(ImagePlus imp) {
ImageProcessor ip;
int type = imp.getType();
if (type != ImagePlus.COLOR_RGB) return null;
ip = imp.getProcessor();
int id = imp.getID();
int slice = imp.getCurrentSlice();
if ((id != previousImageID) | (slice != previousSlice) | (flag)) {
flag = false; // if true, flags a change from HSB to RGB or viceversa
numSlices = imp.getStackSize();
stack = imp.getStack();
width = stack.getWidth();
height = stack.getHeight();
numPixels = width * height;
hSource = new byte[numPixels];
sSource = new byte[numPixels];
bSource = new byte[numPixels];
// restore = (int[])ip.getPixelsCopy(); //This runs into trouble sometimes, so do it the
// long way:
int[] temp = (int[]) ip.getPixels();
restore = new int[numPixels];
for (int i = 0; i < numPixels; i++) restore[i] = temp[i];
fillMask = new int[numPixels];
// Get hsb or rgb from image.
ColorProcessor cp = (ColorProcessor) ip;
IJ.showStatus("Gathering data");
if (isRGB) cp.getRGB(hSource, sSource, bSource);
else cp.getHSB(hSource, sSource, bSource);
IJ.showStatus("done");
// Create a spectrum ColorModel for the Hue histogram plot.
Color c;
byte[] reds = new byte[256];
byte[] greens = new byte[256];
byte[] blues = new byte[256];
for (int i = 0; i < 256; i++) {
c = Color.getHSBColor(i / 255f, 1f, 1f);
reds[i] = (byte) c.getRed();
greens[i] = (byte) c.getGreen();
blues[i] = (byte) c.getBlue();
}
ColorModel cm = new IndexColorModel(8, 256, reds, greens, blues);
// Make an image with just the hue from the RGB image and the spectrum LUT.
// This is just for a hue histogram for the plot. Do not show it.
// ByteProcessor bpHue = new ByteProcessor(width,height,h,cm);
ByteProcessor bpHue = new ByteProcessor(width, height, hSource, cm);
ImagePlus impHue = new ImagePlus("Hue", bpHue);
// impHue.show();
ByteProcessor bpSat = new ByteProcessor(width, height, sSource, cm);
ImagePlus impSat = new ImagePlus("Sat", bpSat);
// impSat.show();
ByteProcessor bpBri = new ByteProcessor(width, height, bSource, cm);
ImagePlus impBri = new ImagePlus("Bri", bpBri);
// impBri.show();
plot.setHistogram(impHue, 0);
splot.setHistogram(impSat, 1);
bplot.setHistogram(impBri, 2);
updateLabels();
updatePlot();
updateScrollBars();
imp.updateAndDraw();
}
previousImageID = id;
previousSlice = slice;
return ip;
}
