示例#1
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#2
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#3
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;
    }