/**
* Execute plugin functionality: stack FFT with window function, max projection over all slices
* (phase, Z angle), blank out central 1/8 circle (set to min value), display min-max.
*/
public ResultSet exec(ImagePlus... imps) {
ImagePlus imp = imps[0];
Util_StackFFT2D stackFFT2D = new Util_StackFFT2D();
stackFFT2D.resultTypeChoice = Util_StackFFT2D.resultType[1];
ImagePlus impF = stackFFT2D.exec(imp);
IJ.run(impF, "Z Project...", "projection=[Max Intensity]");
ImagePlus impProjF = ij.WindowManager.getCurrentImage();
maskCentralRegion(impProjF);
if (impProjF.isComposite()) {
// display grayscale, not colored composite
CompositeImage ci = (CompositeImage) impProjF;
ci.setMode(IJ.GRAYSCALE);
impProjF.updateAndDraw();
}
displayMinToMax(impProjF);
impProjF.setTitle(I1l.makeTitle(imps[0], TLA));
String shortInfo =
"Maximum intensity projection of log"
+ " (amplitude^2) 2D FFT stack, central region masked,"
+ " rescaled (min-max) to improve contrast of the relevant"
+ " frequency range.";
results.addImp(shortInfo, impProjF);
results.addInfo(
"How to interpret",
"look for clean 1st & 2nd"
+ " order spots, similar across angles. Note that spot"
+ " intensity depends on image content.");
return results;
}
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() {
while (!done) {
synchronized (this) {
try {
wait();
} catch (InterruptedException e) {
}
reset(imp, ip); // GL
apply(imp, ip); // GL
imp.updateAndDraw(); // GL
}
}
}
public void actionPerformed(ActionEvent e) {
Button b = (Button) e.getSource();
if (b == null) return;
boolean imageThere = checkImage();
if (imageThere) {
if (b == originalB) {
reset(imp, ip);
filteredB.setEnabled(true);
} else if (b == filteredB) {
apply(imp, ip);
} else if (b == sampleB) {
reset(imp, ip);
sample();
apply(imp, ip);
} else if (b == stackB) {
applyStack();
} else if (b == helpB) {
IJ.showMessage(
"Help",
"Threshold Colour v1.0\n \n"
+ "Modification of Bob Dougherty's BandPass2 plugin by G.Landini to\n"
+ "threshold 24 bit RGB images based on Hue, Saturation and Brightness\n"
+ "or Red, Green and Blue components.\n \n"
+ "Pass: Band-pass filter (anything within range is displayed).\n \n"
+ "Stop: Band-reject filter (anything within range is NOT displayed).\n \n"
+ "Original: Shows the original image and updates the buffer when\n"
+ " switching to another image.\n \n"
+ "Filtered: Shows the filtered image.\n \n"
+ "Stack: Processes the rest of the slices in the stack (if any)\n"
+ " using the current settings.\n \n"
+ "Threshold: Shows the object/background in the foreground and\n"
+ " background colours selected in the ImageJ toolbar.\n \n"
+ "Invert: Swaps the fore/background colours.\n \n"
+ "Sample: (experimental) Sets the ranges of the filters based on the\n"
+ " pixel value componentd in a rectangular, user-defined, ROI.\n \n"
+ "HSB RGB: Selects HSB or RGB space and resets all the filters.\n \n"
+ "Note that the \'thresholded\' image is RGB, not 8 bit grey.");
}
updatePlot();
updateLabels();
imp.updateAndDraw();
} else {
IJ.beep();
IJ.showStatus("No Image");
}
notify();
}
/**
* Execute the plugin functionality: duplicate and scale the given image.
*
* @return an Object[] array with the name and the scaled ImagePlus. Does NOT show the new, image;
* just returns it.
*/
public Object[] exec(
ImagePlus imp, String myMethod, int radius, double par1, double par2, boolean doIwhite) {
// 0 - Check validity of parameters
if (null == imp) return null;
ImageProcessor ip = imp.getProcessor();
int xe = ip.getWidth();
int ye = ip.getHeight();
// int [] data = (ip.getHistogram());
IJ.showStatus("Thresholding...");
long startTime = System.currentTimeMillis();
// 1 Do it
if (imp.getStackSize() == 1) {
ip.snapshot();
Undo.setup(Undo.FILTER, imp);
}
// Apply the selected algorithm
if (myMethod.equals("Bernsen")) {
Bernsen(imp, radius, par1, par2, doIwhite);
} else if (myMethod.equals("Contrast")) {
Contrast(imp, radius, par1, par2, doIwhite);
} else if (myMethod.equals("Mean")) {
Mean(imp, radius, par1, par2, doIwhite);
} else if (myMethod.equals("Median")) {
Median(imp, radius, par1, par2, doIwhite);
} else if (myMethod.equals("MidGrey")) {
MidGrey(imp, radius, par1, par2, doIwhite);
} else if (myMethod.equals("Niblack")) {
Niblack(imp, radius, par1, par2, doIwhite);
} else if (myMethod.equals("Otsu")) {
Otsu(imp, radius, par1, par2, doIwhite);
} else if (myMethod.equals("Phansalkar")) {
Phansalkar(imp, radius, par1, par2, doIwhite);
} else if (myMethod.equals("Sauvola")) {
Sauvola(imp, radius, par1, par2, doIwhite);
}
// IJ.showProgress((double)(255-i)/255);
imp.updateAndDraw();
imp.getProcessor().setThreshold(255, 255, ImageProcessor.NO_LUT_UPDATE);
// 2 - Return the threshold and the image
IJ.showStatus("\nDone " + (System.currentTimeMillis() - startTime) / 1000.0);
return new Object[] {imp};
}
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"); }
/** Ask for parameters and then execute. */
public void run(String arg) {
// 1 - Obtain the currently active image:
ImagePlus imp = IJ.getImage();
if (null == imp) {
IJ.showMessage("There must be at least one image open");
return;
}
if (imp.getBitDepth() != 8) {
IJ.showMessage("Error", "Only 8-bit images are supported");
return;
}
// 2 - Ask for parameters:
GenericDialog gd = new GenericDialog("Auto Local Threshold");
String[] methods = {
"Try all",
"Bernsen",
"Contrast",
"Mean",
"Median",
"MidGrey",
"Niblack",
"Otsu",
"Phansalkar",
"Sauvola"
};
gd.addMessage("Auto Local Threshold v1.5");
gd.addChoice("Method", methods, methods[0]);
gd.addNumericField("Radius", 15, 0);
gd.addMessage("Special paramters (if different from default)");
gd.addNumericField("Parameter_1", 0, 0);
gd.addNumericField("Parameter_2", 0, 0);
gd.addCheckbox("White objects on black background", true);
if (imp.getStackSize() > 1) {
gd.addCheckbox("Stack", false);
}
gd.addMessage("Thresholded result is always shown in white [255].");
gd.showDialog();
if (gd.wasCanceled()) return;
// 3 - Retrieve parameters from the dialog
String myMethod = gd.getNextChoice();
int radius = (int) gd.getNextNumber();
double par1 = (double) gd.getNextNumber();
double par2 = (double) gd.getNextNumber();
boolean doIwhite = gd.getNextBoolean();
boolean doIstack = false;
int stackSize = imp.getStackSize();
if (stackSize > 1) doIstack = gd.getNextBoolean();
// 4 - Execute!
// long start = System.currentTimeMillis();
if (myMethod.equals("Try all")) {
ImageProcessor ip = imp.getProcessor();
int xe = ip.getWidth();
int ye = ip.getHeight();
int ml = methods.length;
ImagePlus imp2, imp3;
ImageStack tstack = null, stackNew;
if (stackSize > 1 && doIstack) {
boolean doItAnyway = true;
if (stackSize > 25) {
YesNoCancelDialog d =
new YesNoCancelDialog(
IJ.getInstance(),
"Auto Local Threshold",
"You might run out of memory.\n \nDisplay "
+ stackSize
+ " slices?\n \n \'No\' will process without display and\noutput results to the log window.");
if (!d.yesPressed()) {
// doIlog=true; //will show in the log window
doItAnyway = false;
}
if (d.cancelPressed()) return;
}
for (int j = 1; j <= stackSize; j++) {
imp.setSlice(j);
ip = imp.getProcessor();
tstack = new ImageStack(xe, ye);
for (int k = 1; k < ml; k++) tstack.addSlice(methods[k], ip.duplicate());
imp2 = new ImagePlus("Auto Threshold", tstack);
imp2.updateAndDraw();
for (int k = 1; k < ml; k++) {
imp2.setSlice(k);
Object[] result = exec(imp2, methods[k], radius, par1, par2, doIwhite);
}
// if (doItAnyway){
CanvasResizer cr = new CanvasResizer();
stackNew = cr.expandStack(tstack, (xe + 2), (ye + 18), 1, 1);
imp3 = new ImagePlus("Auto Threshold", stackNew);
imp3.updateAndDraw();
MontageMaker mm = new MontageMaker();
mm.makeMontage(imp3, 3, 3, 1.0, 1, (ml - 1), 1, 0, true); // 3 columns and 3 rows
}
imp.setSlice(1);
// if (doItAnyway)
IJ.run("Images to Stack", "method=[Copy (center)] title=Montage");
return;
} else { // single image try all
tstack = new ImageStack(xe, ye);
for (int k = 1; k < ml; k++) tstack.addSlice(methods[k], ip.duplicate());
imp2 = new ImagePlus("Auto Threshold", tstack);
imp2.updateAndDraw();
for (int k = 1; k < ml; k++) {
imp2.setSlice(k);
// IJ.log("analyzing slice with "+methods[k]);
Object[] result = exec(imp2, methods[k], radius, par1, par2, doIwhite);
}
// imp2.setSlice(1);
CanvasResizer cr = new CanvasResizer();
stackNew = cr.expandStack(tstack, (xe + 2), (ye + 18), 1, 1);
imp3 = new ImagePlus("Auto Threshold", stackNew);
imp3.updateAndDraw();
MontageMaker mm = new MontageMaker();
mm.makeMontage(imp3, 3, 3, 1.0, 1, (ml - 1), 1, 0, true);
return;
}
} else { // selected a method
if (stackSize > 1 && doIstack) { // whole stack
// if (doIstackHistogram) {// one global histogram
// Object[] result = exec(imp, myMethod, noWhite, noBlack, doIwhite, doIset, doIlog,
// doIstackHistogram );
// }
// else{ // slice by slice
for (int k = 1; k <= stackSize; k++) {
imp.setSlice(k);
Object[] result = exec(imp, myMethod, radius, par1, par2, doIwhite);
}
// }
imp.setSlice(1);
} else { // just one slice
Object[] result = exec(imp, myMethod, radius, par1, par2, doIwhite);
}
// 5 - If all went well, show the image:
// not needed here as the source image is binarised
}
}
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;
}