/**
  * 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;
 }
示例#2
0
  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();
  }
示例#3
0
 public void run() {
   while (!done) {
     synchronized (this) {
       try {
         wait();
       } catch (InterruptedException e) {
       }
       reset(imp, ip); // GL
       apply(imp, ip); // GL
       imp.updateAndDraw(); // GL
     }
   }
 }
示例#4
0
    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();
    }
示例#5
0
  /**
   * 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};
  }
示例#6
0
	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");        }      
示例#7
0
  /** 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
    }
  }
示例#8
0
    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;
    }