void lineToArea(ImagePlus imp) {
Roi roi = imp.getRoi();
if (roi == null || !roi.isLine()) {
IJ.error("Line to Area", "Line selection required");
return;
}
Undo.setup(Undo.ROI, imp);
Roi roi2 = null;
if (roi.getType() == Roi.LINE) {
double width = roi.getStrokeWidth();
if (width <= 1.0) roi.setStrokeWidth(1.0000001);
FloatPolygon p = roi.getFloatPolygon();
roi.setStrokeWidth(width);
roi2 = new PolygonRoi(p, Roi.POLYGON);
roi2.setDrawOffset(roi.getDrawOffset());
} else {
ImageProcessor ip2 = new ByteProcessor(imp.getWidth(), imp.getHeight());
ip2.setColor(255);
roi.drawPixels(ip2);
// new ImagePlus("ip2", ip2.duplicate()).show();
ip2.setThreshold(255, 255, ImageProcessor.NO_LUT_UPDATE);
ThresholdToSelection tts = new ThresholdToSelection();
roi2 = tts.convert(ip2);
}
transferProperties(roi, roi2);
roi2.setStrokeWidth(0);
Color c = roi2.getStrokeColor();
if (c != null) // remove any transparency
roi2.setStrokeColor(new Color(c.getRed(), c.getGreen(), c.getBlue()));
imp.setRoi(roi2);
Roi.previousRoi = (Roi) roi.clone();
}
void createMask(ImagePlus imp) {
Roi roi = imp.getRoi();
boolean useInvertingLut = Prefs.useInvertingLut;
Prefs.useInvertingLut = false;
if (roi == null || !(roi.isArea() || roi.getType() == Roi.POINT)) {
createMaskFromThreshold(imp);
Prefs.useInvertingLut = useInvertingLut;
return;
}
ImagePlus maskImp = null;
Frame frame = WindowManager.getFrame("Mask");
if (frame != null && (frame instanceof ImageWindow))
maskImp = ((ImageWindow) frame).getImagePlus();
if (maskImp == null) {
ImageProcessor ip = new ByteProcessor(imp.getWidth(), imp.getHeight());
if (!Prefs.blackBackground) ip.invertLut();
maskImp = new ImagePlus("Mask", ip);
maskImp.show();
}
ImageProcessor ip = maskImp.getProcessor();
ip.setRoi(roi);
ip.setValue(255);
ip.fill(ip.getMask());
maskImp.updateAndDraw();
Prefs.useInvertingLut = useInvertingLut;
}
public void run(String arg) {
imp = WindowManager.getCurrentImage();
if (arg.equals("add")) {
addToRoiManager(imp);
return;
}
if (imp == null) {
IJ.noImage();
return;
}
if (arg.equals("all")) imp.setRoi(0, 0, imp.getWidth(), imp.getHeight());
else if (arg.equals("none")) imp.killRoi();
else if (arg.equals("restore")) imp.restoreRoi();
else if (arg.equals("spline")) fitSpline();
else if (arg.equals("circle")) fitCircle(imp);
else if (arg.equals("ellipse")) createEllipse(imp);
else if (arg.equals("hull")) convexHull(imp);
else if (arg.equals("mask")) createMask(imp);
else if (arg.equals("from")) createSelectionFromMask(imp);
else if (arg.equals("inverse")) invert(imp);
else if (arg.equals("toarea")) lineToArea(imp);
else if (arg.equals("toline")) areaToLine(imp);
else if (arg.equals("properties")) {
setProperties("Properties ", imp.getRoi());
imp.draw();
} else if (arg.equals("band")) makeBand(imp);
else if (arg.equals("tobox")) toBoundingBox(imp);
else runMacro(arg);
}
/** Generate output image whose type is same as input image. */
private ImagePlus makeOutputImage(ImagePlus imp, FloatProcessor fp, int ptype) {
int width = imp.getWidth();
int height = imp.getHeight();
float[] pixels = (float[]) fp.getPixels();
ImageProcessor oip = null;
// Create output image consistent w/ type of input image.
int size = pixels.length;
switch (ptype) {
case BYTE_TYPE:
oip = imp.getProcessor().createProcessor(width, height);
byte[] pixels8 = (byte[]) oip.getPixels();
for (int i = 0; i < size; i++) pixels8[i] = (byte) pixels[i];
break;
case SHORT_TYPE:
oip = imp.getProcessor().createProcessor(width, height);
short[] pixels16 = (short[]) oip.getPixels();
for (int i = 0; i < size; i++) pixels16[i] = (short) pixels[i];
break;
case FLOAT_TYPE:
oip = new FloatProcessor(width, height, pixels, null);
break;
}
// Adjust for display.
// Calling this on non-ByteProcessors ensures image
// processor is set up to correctly display image.
oip.resetMinAndMax();
// Create new image plus object. Don't use
// ImagePlus.createImagePlus here because there may be
// attributes of input image that are not appropriate for
// projection.
return new ImagePlus(makeTitle(), oip);
}
public boolean beadCalibration3d() {
imp = IJ.getImage();
if (imp == null) {
IJ.noImage();
return false;
} else if (imp.getStackSize() == 1) {
IJ.error("Stack required");
return false;
} else if (imp.getType() != ImagePlus.GRAY8 && imp.getType() != ImagePlus.GRAY16) {
// In order to support 32bit images, pict[] must be changed to float[], and getPixel(x, y);
// requires a Float.intBitsToFloat() conversion
IJ.error("8 or 16 bit greyscale image required");
return false;
}
width = imp.getWidth();
height = imp.getHeight();
nslices = imp.getStackSize();
imtitle = imp.getTitle();
models[0] = "*None*";
models[1] = "line";
models[2] = "2nd degree polynomial";
models[3] = "3rd degree polynomial";
models[4] = "4th degree polynomial";
GenericDialog gd = new GenericDialog("3D PALM calibration");
gd.addNumericField("Maximum FWHM (in px)", prefs.get("QuickPALM.3Dcal_fwhm", 20), 0);
gd.addNumericField(
"Particle local threshold (% maximum intensity)", prefs.get("QuickPALM.pthrsh", 20), 0);
gd.addNumericField("Z-spacing (nm)", prefs.get("QuickPALM.z-step", 10), 2);
gd.addNumericField("Calibration Z-smoothing (radius)", prefs.get("QuickPALM.window", 1), 0);
gd.addChoice("Model", models, prefs.get("QuickPALM.model", models[3]));
gd.addCheckbox(
"Show divergence of bead positions against model",
prefs.get("QuickPALM.3Dcal_showDivergence", false));
gd.addCheckbox("Show extra particle info", prefs.get("QuickPALM.3Dcal_showExtraInfo", false));
gd.addMessage("\n\nDon't forget to save the table in the end...");
gd.showDialog();
if (gd.wasCanceled()) return false;
fwhm = gd.getNextNumber();
prefs.set("QuickPALM.QuickPALM.3Dcal_fwhm", fwhm);
pthrsh = gd.getNextNumber() / 100;
prefs.set("QuickPALM.pthrsh", pthrsh * 100);
cal_z = gd.getNextNumber();
prefs.set("QuickPALM.z-step", cal_z);
window = (int) gd.getNextNumber();
prefs.set("QuickPALM.window", window);
model = gd.getNextChoice();
prefs.set("QuickPALM.model", model);
part_divergence = gd.getNextBoolean();
prefs.set("QuickPALM.3Dcal_showDivergence", part_divergence);
part_extrainfo = gd.getNextBoolean();
prefs.set("QuickPALM.3Dcal_showExtraInfo", part_extrainfo);
return true;
}
/** Performs actual projection using specified method. */
public void doProjection() {
if (imp == null) return;
sliceCount = 0;
if (method < AVG_METHOD || method > MEDIAN_METHOD) method = AVG_METHOD;
for (int slice = startSlice; slice <= stopSlice; slice += increment) sliceCount++;
if (method == MEDIAN_METHOD) {
projImage = doMedianProjection();
return;
}
// Create new float processor for projected pixels.
FloatProcessor fp = new FloatProcessor(imp.getWidth(), imp.getHeight());
ImageStack stack = imp.getStack();
RayFunction rayFunc = getRayFunction(method, fp);
if (IJ.debugMode == true) {
IJ.log("\nProjecting stack from: " + startSlice + " to: " + stopSlice);
}
// Determine type of input image. Explicit determination of
// processor type is required for subsequent pixel
// manipulation. This approach is more efficient than the
// more general use of ImageProcessor's getPixelValue and
// putPixel methods.
int ptype;
if (stack.getProcessor(1) instanceof ByteProcessor) ptype = BYTE_TYPE;
else if (stack.getProcessor(1) instanceof ShortProcessor) ptype = SHORT_TYPE;
else if (stack.getProcessor(1) instanceof FloatProcessor) ptype = FLOAT_TYPE;
else {
IJ.error("Z Project", "Non-RGB stack required");
return;
}
// Do the projection.
for (int n = startSlice; n <= stopSlice; n += increment) {
IJ.showStatus("ZProjection " + color + ": " + n + "/" + stopSlice);
IJ.showProgress(n - startSlice, stopSlice - startSlice);
projectSlice(stack.getPixels(n), rayFunc, ptype);
}
// Finish up projection.
if (method == SUM_METHOD) {
fp.resetMinAndMax();
projImage = new ImagePlus(makeTitle(), fp);
} else if (method == SD_METHOD) {
rayFunc.postProcess();
fp.resetMinAndMax();
projImage = new ImagePlus(makeTitle(), fp);
} else {
rayFunc.postProcess();
projImage = makeOutputImage(imp, fp, ptype);
}
if (projImage == null) IJ.error("Z Project", "Error computing projection.");
}
void invert(ImagePlus imp) {
Roi roi = imp.getRoi();
if (roi == null || !roi.isArea()) {
IJ.error("Inverse", "Area selection required");
return;
}
ShapeRoi s1, s2;
if (roi instanceof ShapeRoi) s1 = (ShapeRoi) roi;
else s1 = new ShapeRoi(roi);
s2 = new ShapeRoi(new Roi(0, 0, imp.getWidth(), imp.getHeight()));
imp.setRoi(s1.xor(s2));
}
void createMask(ImagePlus imp) {
Roi roi = imp.getRoi();
boolean useInvertingLut = Prefs.useInvertingLut;
Prefs.useInvertingLut = false;
boolean selectAll =
roi != null
&& roi.getType() == Roi.RECTANGLE
&& roi.getBounds().width == imp.getWidth()
&& roi.getBounds().height == imp.getHeight()
&& imp.isThreshold();
if (roi == null || !(roi.isArea() || roi.getType() == Roi.POINT) || selectAll) {
createMaskFromThreshold(imp);
Prefs.useInvertingLut = useInvertingLut;
return;
}
ImagePlus maskImp = null;
Frame frame = WindowManager.getFrame("Mask");
if (frame != null && (frame instanceof ImageWindow))
maskImp = ((ImageWindow) frame).getImagePlus();
if (maskImp == null) {
ImageProcessor ip = new ByteProcessor(imp.getWidth(), imp.getHeight());
if (!Prefs.blackBackground) ip.invertLut();
maskImp = new ImagePlus("Mask", ip);
maskImp.show();
}
ImageProcessor ip = maskImp.getProcessor();
ip.setRoi(roi);
ip.setValue(255);
ip.fill(ip.getMask());
Calibration cal = imp.getCalibration();
if (cal.scaled()) {
Calibration cal2 = maskImp.getCalibration();
cal2.pixelWidth = cal.pixelWidth;
cal2.pixelHeight = cal.pixelHeight;
cal2.setUnit(cal.getUnit());
}
maskImp.updateAndRepaintWindow();
Prefs.useInvertingLut = useInvertingLut;
}
void lineToArea(ImagePlus imp) {
Roi roi = imp.getRoi();
if (roi == null || !roi.isLine()) {
IJ.error("Line to Area", "Line selection required");
return;
}
ImageProcessor ip2 = new ByteProcessor(imp.getWidth(), imp.getHeight());
ip2.setColor(255);
if (roi.getType() == Roi.LINE && roi.getStrokeWidth() > 1) ip2.fillPolygon(roi.getPolygon());
else roi.drawPixels(ip2);
// new ImagePlus("ip2", ip2.duplicate()).show();
ip2.setThreshold(255, 255, ImageProcessor.NO_LUT_UPDATE);
ThresholdToSelection tts = new ThresholdToSelection();
Roi roi2 = tts.convert(ip2);
imp.setRoi(roi2);
Roi.previousRoi = (Roi) roi.clone();
}
private void doRGBProjection(ImageStack stack) {
ImageStack[] channels = ChannelSplitter.splitRGB(stack, true);
ImagePlus red = new ImagePlus("Red", channels[0]);
ImagePlus green = new ImagePlus("Green", channels[1]);
ImagePlus blue = new ImagePlus("Blue", channels[2]);
imp.unlock();
ImagePlus saveImp = imp;
imp = red;
color = "(red)";
doProjection();
ImagePlus red2 = projImage;
imp = green;
color = "(green)";
doProjection();
ImagePlus green2 = projImage;
imp = blue;
color = "(blue)";
doProjection();
ImagePlus blue2 = projImage;
int w = red2.getWidth(), h = red2.getHeight(), d = red2.getStackSize();
if (method == SD_METHOD) {
ImageProcessor r = red2.getProcessor();
ImageProcessor g = green2.getProcessor();
ImageProcessor b = blue2.getProcessor();
double max = 0;
double rmax = r.getStatistics().max;
if (rmax > max) max = rmax;
double gmax = g.getStatistics().max;
if (gmax > max) max = gmax;
double bmax = b.getStatistics().max;
if (bmax > max) max = bmax;
double scale = 255 / max;
r.multiply(scale);
g.multiply(scale);
b.multiply(scale);
red2.setProcessor(r.convertToByte(false));
green2.setProcessor(g.convertToByte(false));
blue2.setProcessor(b.convertToByte(false));
}
RGBStackMerge merge = new RGBStackMerge();
ImageStack stack2 =
merge.mergeStacks(w, h, d, red2.getStack(), green2.getStack(), blue2.getStack(), true);
imp = saveImp;
projImage = new ImagePlus(makeTitle(), stack2);
}
public void doHyperStackProjection(boolean allTimeFrames) {
int start = startSlice;
int stop = stopSlice;
int firstFrame = 1;
int lastFrame = imp.getNFrames();
if (!allTimeFrames) firstFrame = lastFrame = imp.getFrame();
ImageStack stack = new ImageStack(imp.getWidth(), imp.getHeight());
int channels = imp.getNChannels();
int slices = imp.getNSlices();
if (slices == 1) {
slices = imp.getNFrames();
firstFrame = lastFrame = 1;
}
int frames = lastFrame - firstFrame + 1;
increment = channels;
boolean rgb = imp.getBitDepth() == 24;
for (int frame = firstFrame; frame <= lastFrame; frame++) {
for (int channel = 1; channel <= channels; channel++) {
startSlice = (frame - 1) * channels * slices + (start - 1) * channels + channel;
stopSlice = (frame - 1) * channels * slices + (stop - 1) * channels + channel;
if (rgb) doHSRGBProjection(imp);
else doProjection();
stack.addSlice(null, projImage.getProcessor());
}
}
projImage = new ImagePlus(makeTitle(), stack);
projImage.setDimensions(channels, 1, frames);
if (channels > 1) {
projImage = new CompositeImage(projImage, 0);
((CompositeImage) projImage).copyLuts(imp);
if (method == SUM_METHOD || method == SD_METHOD)
((CompositeImage) projImage).resetDisplayRanges();
}
if (frames > 1) projImage.setOpenAsHyperStack(true);
Overlay overlay = imp.getOverlay();
if (overlay != null) {
startSlice = start;
stopSlice = stop;
if (imp.getType() == ImagePlus.COLOR_RGB)
projImage.setOverlay(projectRGBHyperStackRois(overlay));
else projImage.setOverlay(projectHyperStackRois(overlay));
}
IJ.showProgress(1, 1);
}
// Finds the index of the upper right point that is guaranteed to be on convex hull
int findFirstPoint(int[] xCoordinates, int[] yCoordinates, int n, ImagePlus imp) {
int smallestY = imp.getHeight();
int x, y;
for (int i = 0; i < n; i++) {
y = yCoordinates[i];
if (y < smallestY) smallestY = y;
}
int smallestX = imp.getWidth();
int p1 = 0;
for (int i = 0; i < n; i++) {
x = xCoordinates[i];
y = yCoordinates[i];
if (y == smallestY && x < smallestX) {
smallestX = x;
p1 = i;
}
}
return p1;
}
private void makeBand(ImagePlus imp) {
Roi roi = imp.getRoi();
if (roi == null) {
noRoi("Make Band");
return;
}
if (!roi.isArea()) {
IJ.error("Make Band", "Area selection required");
return;
}
Calibration cal = imp.getCalibration();
double pixels = bandSize;
double size = pixels * cal.pixelWidth;
int decimalPlaces = 0;
if ((int) size != size) decimalPlaces = 2;
GenericDialog gd = new GenericDialog("Make Band");
gd.addNumericField("Band Size:", size, decimalPlaces, 4, cal.getUnits());
gd.showDialog();
if (gd.wasCanceled()) return;
size = gd.getNextNumber();
if (Double.isNaN(size)) {
IJ.error("Make Band", "invalid number");
return;
}
int n = (int) Math.round(size / cal.pixelWidth);
if (n > 255) {
IJ.error("Make Band", "Cannot make bands wider that 255 pixels");
return;
}
int width = imp.getWidth();
int height = imp.getHeight();
Rectangle r = roi.getBounds();
ImageProcessor ip = roi.getMask();
if (ip == null) {
ip = new ByteProcessor(r.width, r.height);
ip.invert();
}
ImageProcessor mask = new ByteProcessor(width, height);
mask.insert(ip, r.x, r.y);
ImagePlus edm = new ImagePlus("mask", mask);
boolean saveBlackBackground = Prefs.blackBackground;
Prefs.blackBackground = false;
IJ.run(edm, "Distance Map", "");
Prefs.blackBackground = saveBlackBackground;
ip = edm.getProcessor();
ip.setThreshold(0, n, ImageProcessor.NO_LUT_UPDATE);
int xx = -1, yy = -1;
for (int x = r.x; x < r.x + r.width; x++) {
for (int y = r.y; y < r.y + r.height; y++) {
if (ip.getPixel(x, y) < n) {
xx = x;
yy = y;
break;
}
}
if (xx >= 0 || yy >= 0) break;
}
int count = IJ.doWand(edm, xx, yy, 0, null);
if (count <= 0) {
IJ.error("Make Band", "Unable to make band");
return;
}
ShapeRoi roi2 = new ShapeRoi(edm.getRoi());
if (!(roi instanceof ShapeRoi)) roi = new ShapeRoi(roi);
ShapeRoi roi1 = (ShapeRoi) roi;
roi2 = roi2.not(roi1);
imp.setRoi(roi2);
bandSize = n;
}
public void run(ImageProcessor ip) {
String[] imageNames = getOpenImageNames();
if (imageNames[0] == "None") {
IJ.error("need at least 2 binary open images");
return;
}
double previousMinOverlap = Prefs.get("BVTB.BinaryFeatureExtractor.minOverlap", 0);
boolean previousCombine = Prefs.get("BVTB.BinaryFeatureExtractor.combine", false);
GenericDialog gd = new GenericDialog("Binary Feature Extractor");
gd.addChoice("Objects image", imageNames, imageNames[0]);
gd.addChoice("Selector image", imageNames, imageNames[1]);
gd.addNumericField("Object_overlap in % (0=off)", previousMinOverlap, 0, 9, "");
gd.addCheckbox("Combine objects and selectors", previousCombine);
gd.addCheckbox("Count output", true);
gd.addCheckbox("Analysis tables", false);
gd.showDialog();
if (gd.wasCanceled()) {
return;
}
String objectsImgTitle = gd.getNextChoice();
String selectorsImgTitle = gd.getNextChoice();
double minOverlap = gd.getNextNumber();
boolean combineImages = gd.getNextBoolean();
boolean showCountOutput = gd.getNextBoolean();
boolean showAnalysis = gd.getNextBoolean();
if (gd.invalidNumber() || minOverlap < 0 || minOverlap > 100) {
IJ.error("invalid number");
return;
}
Prefs.set("BVTB.BinaryFeatureExtractor.minOverlap", minOverlap);
Prefs.set("BVTB.BinaryFeatureExtractor.combine", combineImages);
if (objectsImgTitle.equals(selectorsImgTitle)) {
IJ.error("images need to be different");
return;
}
ImagePlus objectsImp = WindowManager.getImage(objectsImgTitle);
ImageProcessor objectsIP = objectsImp.getProcessor();
ImagePlus selectorsImp = WindowManager.getImage(selectorsImgTitle);
ImageProcessor selectorsIP = selectorsImp.getProcessor();
if (!objectsIP.isBinary() || !selectorsIP.isBinary()) {
IJ.error("works with 8-bit binary images only");
return;
}
if ((objectsImp.getWidth() != selectorsImp.getWidth())
|| objectsImp.getHeight() != selectorsImp.getHeight()) {
IJ.error("images need to be of the same size");
return;
}
// close any existing RoiManager before instantiating a new one for this analysis
RoiManager oldRM = RoiManager.getInstance2();
if (oldRM != null) {
oldRM.close();
}
RoiManager objectsRM = new RoiManager(true);
ResultsTable objectsRT = new ResultsTable();
ParticleAnalyzer analyzeObjects =
new ParticleAnalyzer(analyzerOptions, measurementFlags, objectsRT, 0.0, 999999999.9);
analyzeObjects.setRoiManager(objectsRM);
analyzeObjects.analyze(objectsImp);
objectsRM.runCommand("Show None");
int objectNumber = objectsRT.getCounter();
Roi[] objectRoi = objectsRM.getRoisAsArray();
ResultsTable measureSelectorsRT = new ResultsTable();
Analyzer overlapAnalyzer = new Analyzer(selectorsImp, measurementFlags, measureSelectorsRT);
ImagePlus outputImp =
IJ.createImage("output", "8-bit black", objectsImp.getWidth(), objectsImp.getHeight(), 1);
ImageProcessor outputIP = outputImp.getProcessor();
double[] measuredOverlap = new double[objectNumber];
outputIP.setValue(255.0);
for (int o = 0; o < objectNumber; o++) {
selectorsImp.killRoi();
selectorsImp.setRoi(objectRoi[o]);
overlapAnalyzer.measure();
measuredOverlap[o] = measureSelectorsRT.getValue("%Area", o);
if (minOverlap != 0.0 && measuredOverlap[o] >= minOverlap) {
outputIP.fill(objectRoi[o]);
finalCount++;
} else if (minOverlap == 0.0 && measuredOverlap[o] > 0.0) {
outputIP.fill(objectRoi[o]);
finalCount++;
}
}
// measureSelectorsRT.show("Objects");
selectorsImp.killRoi();
RoiManager selectorRM = new RoiManager(true);
ResultsTable selectorRT = new ResultsTable();
ParticleAnalyzer.setRoiManager(selectorRM);
ParticleAnalyzer analyzeSelectors =
new ParticleAnalyzer(analyzerOptions, measurementFlags, selectorRT, 0.0, 999999999.9);
analyzeSelectors.analyze(selectorsImp);
selectorRM.runCommand("Show None");
int selectorNumber = selectorRT.getCounter();
if (combineImages) {
outputImp.updateAndDraw();
Roi[] selectorRoi = selectorRM.getRoisAsArray();
ResultsTable measureObjectsRT = new ResultsTable();
Analyzer selectorAnalyzer = new Analyzer(outputImp, measurementFlags, measureObjectsRT);
double[] selectorOverlap = new double[selectorNumber];
outputIP.setValue(255.0);
for (int s = 0; s < selectorNumber; s++) {
outputImp.killRoi();
outputImp.setRoi(selectorRoi[s]);
selectorAnalyzer.measure();
selectorOverlap[s] = measureObjectsRT.getValue("%Area", s);
if (selectorOverlap[s] > 0.0d) {
outputIP.fill(selectorRoi[s]);
}
}
selectorRoi = null;
selectorAnalyzer = null;
measureObjectsRT = null;
}
// selectorRT.show("Selectors");
outputImp.killRoi();
String outputImageTitle = WindowManager.getUniqueName("Extracted_" + objectsImgTitle);
outputImp.setTitle(outputImageTitle);
outputImp.show();
outputImp.changes = true;
if (showCountOutput) {
String[] openTextWindows = WindowManager.getNonImageTitles();
boolean makeNewTable = true;
for (int w = 0; w < openTextWindows.length; w++) {
if (openTextWindows[w].equals("BFE_Results")) {
makeNewTable = false;
}
}
TextWindow existingCountTable = ResultsTable.getResultsWindow();
if (makeNewTable) {
countTable = new ResultsTable();
countTable.setPrecision(0);
countTable.setValue("Image", 0, outputImageTitle);
countTable.setValue("Objects", 0, objectNumber);
countTable.setValue("Selectors", 0, selectorNumber);
countTable.setValue("Extracted", 0, finalCount);
countTable.show("BFE_Results");
} else {
IJ.renameResults("BFE_Results", "Results");
countTable = ResultsTable.getResultsTable();
countTable.setPrecision(0);
countTable.incrementCounter();
countTable.addValue("Image", outputImageTitle);
countTable.addValue("Objects", objectNumber);
countTable.addValue("Selectors", selectorNumber);
countTable.addValue("Extracted", finalCount);
IJ.renameResults("Results", "BFE_Results");
countTable.show("BFE_Results");
}
}
if (showAnalysis) {
ResultsTable extractedRT = new ResultsTable();
ParticleAnalyzer analyzeExtracted =
new ParticleAnalyzer(
ParticleAnalyzer.CLEAR_WORKSHEET | ParticleAnalyzer.RECORD_STARTS,
measurementFlags,
extractedRT,
0.0,
999999999.9);
analyzeExtracted.analyze(outputImp);
objectsRT.show("Objects");
selectorRT.show("Selectors");
extractedRT.show("Extracted");
} else {
objectsRT = null;
selectorRT = null;
}
objectsRM = null;
measureSelectorsRT = null;
analyzeObjects = null;
overlapAnalyzer = null;
objectRoi = null;
selectorRM = null;
objectsImp.killRoi();
objectsImp.changes = false;
selectorsImp.changes = false;
}
void Otsu(ImagePlus imp, int radius, double par1, double par2, boolean doIwhite) {
// Otsu's threshold algorithm
// C++ code by Jordan Bevik <*****@*****.**>
// ported to ImageJ plugin by G.Landini. Same algorithm as in Auto_Threshold, this time on local
// circular regions
int[] data;
int w = imp.getWidth();
int h = imp.getHeight();
int position;
int radiusx2 = radius * 2;
ImageProcessor ip = imp.getProcessor();
byte[] pixels = (byte[]) ip.getPixels();
byte[] pixelsOut =
new byte
[pixels.length]; // need this to avoid changing the image data (and further histograms)
byte object;
byte backg;
if (doIwhite) {
object = (byte) 0xff;
backg = (byte) 0;
} else {
object = (byte) 0;
backg = (byte) 0xff;
}
int k, kStar; // k = the current threshold; kStar = optimal threshold
int N1, N; // N1 = # points with intensity <=k; N = total number of points
double BCV, BCVmax; // The current Between Class Variance and maximum BCV
double num, denom; // temporary bookeeping
int Sk; // The total intensity for all histogram points <=k
int S,
L =
256; // The total intensity of the image. Need to hange here if modifying for >8 bits
// images
int roiy;
Roi roi = new OvalRoi(0, 0, radiusx2, radiusx2);
// ip.setRoi(roi);
for (int y = 0; y < h; y++) {
IJ.showProgress(
(double) (y) / (h - 1)); // this method is slow, so let's show the progress bar
roiy = y - radius;
for (int x = 0; x < w; x++) {
roi.setLocation(x - radius, roiy);
ip.setRoi(roi);
// ip.setRoi(new OvalRoi(x-radius, roiy, radiusx2, radiusx2));
position = x + y * w;
data = ip.getHistogram();
// Initialize values:
S = N = 0;
for (k = 0; k < L; k++) {
S += k * data[k]; // Total histogram intensity
N += data[k]; // Total number of data points
}
Sk = 0;
N1 = data[0]; // The entry for zero intensity
BCV = 0;
BCVmax = 0;
kStar = 0;
// Look at each possible threshold value,
// calculate the between-class variance, and decide if it's a max
for (k = 1; k < L - 1; k++) { // No need to check endpoints k = 0 or k = L-1
Sk += k * data[k];
N1 += data[k];
// The float casting here is to avoid compiler warning about loss of precision and
// will prevent overflow in the case of large saturated images
denom = (double) (N1) * (N - N1); // Maximum value of denom is (N^2)/4 = approx. 3E10
if (denom != 0) {
// Float here is to avoid loss of precision when dividing
num = ((double) N1 / N) * S - Sk; // Maximum value of num = 255*N = approx 8E7
BCV = (num * num) / denom;
} else BCV = 0;
if (BCV >= BCVmax) { // Assign the best threshold found so far
BCVmax = BCV;
kStar = k;
}
}
// kStar += 1; // Use QTI convention that intensity -> 1 if intensity >= k
// (the algorithm was developed for I-> 1 if I <= k.)
// return kStar;
pixelsOut[position] = ((int) (pixels[position] & 0xff) > kStar) ? object : backg;
}
}
for (position = 0; position < w * h; position++)
pixels[position] = pixelsOut[position]; // update with thresholded pixels
}
public int setup(String arg, ImagePlus imp) {
// IJ.register(Average_Oversampled.class);
if (IJ.versionLessThan("1.32c")) return DONE;
if (this.pre) { // before finding means
imp.unlock();
this.imp = imp;
this.nslices = imp.getNSlices();
this.width = imp.getWidth();
this.height = imp.getHeight();
this.slicecols = new float[nslices][width];
this.pre = false;
return (DOES_ALL + DOES_STACKS + FINAL_PROCESSING);
} else { // find SD after finding means of columns
float sum; // sum of pixel values column
float avg; // average pixel value of a column
double devsum; // sum of deviations
double devavg; // standard deviation
double[] columns = new double[width]; // x-axis of plot
double[] sdevs = new double[width]; // y-axis of plot
for (int i = 0; i < width; i += 1) {
sum = 0; // reset with each column
avg = 0; // reset with each column
devsum = 0; // reset with each column
devavg = 0; // reset with each column
columns[i] = i; // building x-axis
for (int s = 0; s < nslices; s += 1) { // sum of column means
sum = sum + slicecols[s][i];
}
avg = sum / nslices; // mean of one column across all slices
for (int s = 0; s < nslices; s += 1) { // standard deviation
devsum = devsum + Math.pow((slicecols[s][i] - avg), 2); // square diff
}
devavg = Math.sqrt(devsum / nslices);
sdevs[i] = devavg; // building y-axis
}
Plot plot = new Plot("Average SD by Column", "Columns", "Standard Deviation", columns, sdevs);
plot.show();
// calculate CTN
double ctn;
double sdevssum = 0;
for (double sd : sdevs) {
sdevssum = sdevssum + sd;
}
ctn = sdevssum / width;
// display CTN on results table
ResultsTable rt = ResultsTable.getResultsTable();
// rt.incrementCounter();
rt.addValue("Column Temporal Noise", ctn);
rt.show("Results");
this.pre = false;
return DONE;
}
}