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();
}
// get a pixel value; returns Float.NaN if outside the field.
private float getPixel(int x, int y) {
if (x < 0 || x >= width || y < 0 || y >= height) return Float.NaN;
if (bpixels != null) return bpixels[y * width + x] & 0xff;
else if (spixels != null) return spixels[y * width + x] & 0xffff;
else if (fpixels != null) return fpixels[y * width + x];
else if (exactPixelValue) // RGB for exact match
return cpixels[y * width + x] & 0xffffff; // don't care for upper byte
else // gray value of RGB
return ip.getPixelValue(x, y);
}
void avg_col(ImageProcessor ip) {
float sum; // sum of pixel values column
float avg; // average pixel value of a column
float[] sliceavgs = new float[width]; // means across columns of one slice
int sliceNumber = ip.getSliceNumber() - 1; // slice number
for (int x = 0; x < width; x += 1) {
sum = 0; // reset with each column
avg = 0; // reset with each column
for (int y = 0; y < height; y += 1) {
sum = sum + ip.getPixelValue(x, y);
}
avg = sum / height;
sliceavgs[x] = avg; // building array of means
}
this.slicecols[sliceNumber] = sliceavgs; // add this slice's means to array
}
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"); }
/**
* Performs particle analysis on the specified ImagePlus and ImageProcessor. Returns false if
* there is an error.
*/
public boolean analyze(ImagePlus imp, ImageProcessor ip) {
if (this.imp == null) this.imp = imp;
showResults = (options & SHOW_RESULTS) != 0;
excludeEdgeParticles = (options & EXCLUDE_EDGE_PARTICLES) != 0;
resetCounter = (options & CLEAR_WORKSHEET) != 0;
showProgress = (options & SHOW_PROGRESS) != 0;
floodFill = (options & INCLUDE_HOLES) == 0;
recordStarts = (options & RECORD_STARTS) != 0;
addToManager = (options & ADD_TO_MANAGER) != 0;
displaySummary = (options & DISPLAY_SUMMARY) != 0;
inSituShow = (options & IN_SITU_SHOW) != 0;
outputImage = null;
ip.snapshot();
ip.setProgressBar(null);
if (Analyzer.isRedirectImage()) {
redirectImp = Analyzer.getRedirectImage(imp);
if (redirectImp == null) return false;
int depth = redirectImp.getStackSize();
if (depth > 1 && depth == imp.getStackSize()) {
ImageStack redirectStack = redirectImp.getStack();
redirectIP = redirectStack.getProcessor(imp.getCurrentSlice());
} else redirectIP = redirectImp.getProcessor();
} else if (imp.getType() == ImagePlus.COLOR_RGB) {
ImagePlus original = (ImagePlus) imp.getProperty("OriginalImage");
if (original != null
&& original.getWidth() == imp.getWidth()
&& original.getHeight() == imp.getHeight()) {
redirectImp = original;
redirectIP = original.getProcessor();
}
}
if (!setThresholdLevels(imp, ip)) return false;
width = ip.getWidth();
height = ip.getHeight();
if (!(showChoice == NOTHING || showChoice == OVERLAY_OUTLINES || showChoice == OVERLAY_MASKS)) {
blackBackground = Prefs.blackBackground && inSituShow;
if (slice == 1) outlines = new ImageStack(width, height);
if (showChoice == ROI_MASKS) drawIP = new ShortProcessor(width, height);
else drawIP = new ByteProcessor(width, height);
drawIP.setLineWidth(lineWidth);
if (showChoice == ROI_MASKS) {
} // Place holder for now...
else if (showChoice == MASKS && !blackBackground) drawIP.invertLut();
else if (showChoice == OUTLINES) {
if (!inSituShow) {
if (customLut == null) makeCustomLut();
drawIP.setColorModel(customLut);
}
drawIP.setFont(new Font("SansSerif", Font.PLAIN, fontSize));
if (fontSize > 12 && inSituShow) drawIP.setAntialiasedText(true);
}
outlines.addSlice(null, drawIP);
if (showChoice == ROI_MASKS || blackBackground) {
drawIP.setColor(Color.black);
drawIP.fill();
drawIP.setColor(Color.white);
} else {
drawIP.setColor(Color.white);
drawIP.fill();
drawIP.setColor(Color.black);
}
}
calibration = redirectImp != null ? redirectImp.getCalibration() : imp.getCalibration();
if (rt == null) {
rt = Analyzer.getResultsTable();
analyzer = new Analyzer(imp);
} else analyzer = new Analyzer(imp, measurements, rt);
if (resetCounter && slice == 1) {
if (!Analyzer.resetCounter()) return false;
}
beginningCount = Analyzer.getCounter();
byte[] pixels = null;
if (ip instanceof ByteProcessor) pixels = (byte[]) ip.getPixels();
if (r == null) {
r = ip.getRoi();
mask = ip.getMask();
if (displaySummary) {
if (mask != null) totalArea = ImageStatistics.getStatistics(ip, AREA, calibration).area;
else totalArea = r.width * calibration.pixelWidth * r.height * calibration.pixelHeight;
}
}
minX = r.x;
maxX = r.x + r.width;
minY = r.y;
maxY = r.y + r.height;
if (r.width < width || r.height < height || mask != null) {
if (!eraseOutsideRoi(ip, r, mask)) return false;
}
int offset;
double value;
int inc = Math.max(r.height / 25, 1);
int mi = 0;
ImageWindow win = imp.getWindow();
if (win != null) win.running = true;
if (measurements == 0) measurements = Analyzer.getMeasurements();
if (showChoice == ELLIPSES) measurements |= ELLIPSE;
measurements &= ~LIMIT; // ignore "Limit to Threshold"
roiNeedsImage =
(measurements & PERIMETER) != 0
|| (measurements & SHAPE_DESCRIPTORS) != 0
|| (measurements & FERET) != 0;
particleCount = 0;
wand = new Wand(ip);
pf = new PolygonFiller();
if (floodFill) {
ImageProcessor ipf = ip.duplicate();
ipf.setValue(fillColor);
ff = new FloodFiller(ipf);
}
roiType = Wand.allPoints() ? Roi.FREEROI : Roi.TRACED_ROI;
for (int y = r.y; y < (r.y + r.height); y++) {
offset = y * width;
for (int x = r.x; x < (r.x + r.width); x++) {
if (pixels != null) value = pixels[offset + x] & 255;
else if (imageType == SHORT) value = ip.getPixel(x, y);
else value = ip.getPixelValue(x, y);
if (value >= level1 && value <= level2) analyzeParticle(x, y, imp, ip);
}
if (showProgress && ((y % inc) == 0)) IJ.showProgress((double) (y - r.y) / r.height);
if (win != null) canceled = !win.running;
if (canceled) {
Macro.abort();
break;
}
}
if (showProgress) IJ.showProgress(1.0);
if (showResults) rt.updateResults();
imp.killRoi();
ip.resetRoi();
ip.reset();
if (displaySummary && IJ.getInstance() != null) updateSliceSummary();
if (addToManager && roiManager != null) roiManager.setEditMode(imp, true);
maxParticleCount = (particleCount > maxParticleCount) ? particleCount : maxParticleCount;
totalCount += particleCount;
if (!canceled) showResults();
return true;
}
