/** 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);
}
void Bernsen(ImagePlus imp, int radius, double par1, double par2, boolean doIwhite) {
// Bernsen recommends WIN_SIZE = 31 and CONTRAST_THRESHOLD = 15.
// 1) Bernsen J. (1986) "Dynamic Thresholding of Grey-Level Images"
// Proc. of the 8th Int. Conf. on Pattern Recognition, pp. 1251-1255
// 2) Sezgin M. and Sankur B. (2004) "Survey over Image Thresholding
// Techniques and Quantitative Performance Evaluation" Journal of
// Electronic Imaging, 13(1): 146-165
// http://citeseer.ist.psu.edu/sezgin04survey.html
// Ported to ImageJ plugin from E Celebi's fourier_0.8 routines
// This version uses a circular local window, instead of a rectagular one
ImagePlus Maximp, Minimp;
ImageProcessor ip = imp.getProcessor(), ipMax, ipMin;
int contrast_threshold = 15;
int local_contrast;
int mid_gray;
byte object;
byte backg;
int temp;
if (par1 != 0) {
IJ.log("Bernsen: changed contrast_threshold from :" + contrast_threshold + " to:" + par1);
contrast_threshold = (int) par1;
}
if (doIwhite) {
object = (byte) 0xff;
backg = (byte) 0;
} else {
object = (byte) 0;
backg = (byte) 0xff;
}
Maximp = duplicateImage(ip);
ipMax = Maximp.getProcessor();
RankFilters rf = new RankFilters();
rf.rank(ipMax, radius, rf.MAX); // Maximum
// Maximp.show();
Minimp = duplicateImage(ip);
ipMin = Minimp.getProcessor();
rf.rank(ipMin, radius, rf.MIN); // Minimum
// Minimp.show();
byte[] pixels = (byte[]) ip.getPixels();
byte[] max = (byte[]) ipMax.getPixels();
byte[] min = (byte[]) ipMin.getPixels();
for (int i = 0; i < pixels.length; i++) {
local_contrast = (int) ((max[i] & 0xff) - (min[i] & 0xff));
mid_gray = (int) ((min[i] & 0xff) + (max[i] & 0xff)) / 2;
temp = (int) (pixels[i] & 0x0000ff);
if (local_contrast < contrast_threshold)
pixels[i] = (mid_gray >= 128) ? object : backg; // Low contrast region
else pixels[i] = (temp >= mid_gray) ? object : backg;
}
// imp.updateAndDraw();
return;
}
void createMaskFromThreshold(ImagePlus imp) {
ImageProcessor ip = imp.getProcessor();
if (ip.getMinThreshold() == ImageProcessor.NO_THRESHOLD) {
IJ.error("Create Mask", "Area selection or thresholded image required");
return;
}
double t1 = ip.getMinThreshold();
double t2 = ip.getMaxThreshold();
IJ.run("Duplicate...", "title=mask");
ImagePlus imp2 = WindowManager.getCurrentImage();
ImageProcessor ip2 = imp2.getProcessor();
ip2.setThreshold(t1, t2, ImageProcessor.NO_LUT_UPDATE);
IJ.run("Convert to Mask");
}
void createEllipse(ImagePlus imp) {
IJ.showStatus("Fitting ellipse");
Roi roi = imp.getRoi();
if (roi == null) {
noRoi("Fit Ellipse");
return;
}
if (roi.isLine()) {
IJ.error("Fit Ellipse", "\"Fit Ellipse\" does not work with line selections");
return;
}
ImageProcessor ip = imp.getProcessor();
ip.setRoi(roi);
int options = Measurements.CENTROID + Measurements.ELLIPSE;
ImageStatistics stats = ImageStatistics.getStatistics(ip, options, null);
double dx = stats.major * Math.cos(stats.angle / 180.0 * Math.PI) / 2.0;
double dy = -stats.major * Math.sin(stats.angle / 180.0 * Math.PI) / 2.0;
double x1 = stats.xCentroid - dx;
double x2 = stats.xCentroid + dx;
double y1 = stats.yCentroid - dy;
double y2 = stats.yCentroid + dy;
double aspectRatio = stats.minor / stats.major;
imp.killRoi();
imp.setRoi(new EllipseRoi(x1, y1, x2, y2, aspectRatio));
}
public int showDialog(ImagePlus imp, String command, PlugInFilterRunner pfr) {
if (doOptions) {
this.imp = imp;
this.pfr = pfr;
GenericDialog gd = new GenericDialog("Binary Options");
gd.addNumericField("Iterations (1-" + MAX_ITERATIONS + "):", iterations, 0, 3, "");
gd.addNumericField("Count (1-8):", count, 0, 3, "");
gd.addCheckbox("Black background", Prefs.blackBackground);
gd.addCheckbox("Pad edges when eroding", Prefs.padEdges);
gd.addChoice("EDM output:", outputTypes, outputTypes[EDM.getOutputType()]);
if (imp != null) {
gd.addChoice("Do:", operations, operation);
gd.addPreviewCheckbox(pfr);
gd.addDialogListener(this);
previewing = true;
}
gd.addHelp(IJ.URL + "/docs/menus/process.html#options");
gd.showDialog();
previewing = false;
if (gd.wasCanceled()) return DONE;
if (imp == null) { // options dialog only, no do/preview
dialogItemChanged(gd, null); // read dialog result
return DONE;
}
return operation.equals(NO_OPERATION) ? DONE : IJ.setupDialog(imp, flags);
} else { // no dialog, 'arg' is operation type
if (!((ByteProcessor) imp.getProcessor()).isBinary()) {
IJ.error("8-bit binary (black and white only) image required.");
return DONE;
}
return IJ.setupDialog(imp, flags);
}
}
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(ImageProcessor ip) {
if (enlarge && gd.wasOKed())
synchronized (this) {
if (!isEnlarged) {
enlargeCanvas();
isEnlarged = true;
}
}
if (isEnlarged) { // enlarging may have made the ImageProcessor invalid, also for the parallel
// threads
int slice = pfr.getSliceNumber();
if (imp.getStackSize() == 1) ip = imp.getProcessor();
else ip = imp.getStack().getProcessor(slice);
}
ip.setInterpolationMethod(interpolationMethod);
if (fillWithBackground) {
Color bgc = Toolbar.getBackgroundColor();
if (bitDepth == 8) ip.setBackgroundValue(ip.getBestIndex(bgc));
else if (bitDepth == 24) ip.setBackgroundValue(bgc.getRGB());
} else ip.setBackgroundValue(0);
ip.rotate(angle);
if (!gd.wasOKed()) drawGridLines(gridLines);
if (isEnlarged && imp.getStackSize() == 1) {
imp.changes = true;
imp.updateAndDraw();
Undo.setup(Undo.COMPOUND_FILTER_DONE, imp);
}
}
/**
* Prepare for processing; also called at the very end with argument 'final' to show any newly
* created output image.
*/
public int setup(String arg, ImagePlus imp) {
if (arg.equals("final")) {
showOutput();
return DONE;
}
this.imp = imp;
// 'arg' is processing type; default is 'EDM' (0)
if (arg.equals("watershed")) {
processType = WATERSHED;
flags += KEEP_THRESHOLD;
} else if (arg.equals("points")) processType = UEP;
else if (arg.equals("voronoi")) processType = VORONOI;
// output type
if (processType != WATERSHED) // Watershed always has output BYTE_OVERWRITE=0
outImageType = outputType; // otherwise use the static variable from setOutputType
if (outImageType != BYTE_OVERWRITE) flags |= NO_CHANGES;
// check image and prepare
if (imp != null) {
ImageProcessor ip = imp.getProcessor();
if (!ip.isBinary()) {
IJ.error("8-bit binary image (0 and 255) required.");
return DONE;
}
ip.resetRoi();
// processing routines assume background=0; image may be otherwise
boolean invertedLut = imp.isInvertedLut();
background255 =
(invertedLut && Prefs.blackBackground) || (!invertedLut && !Prefs.blackBackground);
}
return flags;
} // public int setup
private ImagePlus duplicateImage(ImageProcessor iProcessor) {
int w = iProcessor.getWidth();
int h = iProcessor.getHeight();
ImagePlus iPlus = NewImage.createByteImage("Image", w, h, 1, NewImage.FILL_BLACK);
ImageProcessor imageProcessor = iPlus.getProcessor();
imageProcessor.copyBits(iProcessor, 0, 0, Blitter.COPY);
return iPlus;
}
void Contrast(ImagePlus imp, int radius, double par1, double par2, boolean doIwhite) {
// G. Landini, 2013
// Based on a simple contrast toggle. This procedure does not have user-provided paramters other
// than the kernel radius
// Sets the pixel value to either white or black depending on whether its current value is
// closest to the local Max or Min respectively
// The procedure is similar to Toggle Contrast Enhancement (see Soille, Morphological Image
// Analysis (2004), p. 259
ImagePlus Maximp, Minimp;
ImageProcessor ip = imp.getProcessor(), ipMax, ipMin;
int c_value = 0;
int mid_gray;
byte object;
byte backg;
if (doIwhite) {
object = (byte) 0xff;
backg = (byte) 0;
} else {
object = (byte) 0;
backg = (byte) 0xff;
}
Maximp = duplicateImage(ip);
ipMax = Maximp.getProcessor();
RankFilters rf = new RankFilters();
rf.rank(ipMax, radius, rf.MAX); // Maximum
// Maximp.show();
Minimp = duplicateImage(ip);
ipMin = Minimp.getProcessor();
rf.rank(ipMin, radius, rf.MIN); // Minimum
// Minimp.show();
byte[] pixels = (byte[]) ip.getPixels();
byte[] max = (byte[]) ipMax.getPixels();
byte[] min = (byte[]) ipMin.getPixels();
for (int i = 0; i < pixels.length; i++) {
pixels[i] =
((Math.abs((int) (max[i] & 0xff - pixels[i] & 0xff))
<= Math.abs((int) (pixels[i] & 0xff - min[i] & 0xff))))
? object
: backg;
}
// imp.updateAndDraw();
return;
}
void MidGrey(ImagePlus imp, int radius, double par1, double par2, boolean doIwhite) {
// See: Image Processing Learning Resourches HIPR2
// http://homepages.inf.ed.ac.uk/rbf/HIPR2/adpthrsh.htm
ImagePlus Maximp, Minimp;
ImageProcessor ip = imp.getProcessor(), ipMax, ipMin;
int c_value = 0;
int mid_gray;
byte object;
byte backg;
if (par1 != 0) {
IJ.log("MidGrey: changed c_value from :" + c_value + " to:" + par1);
c_value = (int) par1;
}
if (doIwhite) {
object = (byte) 0xff;
backg = (byte) 0;
} else {
object = (byte) 0;
backg = (byte) 0xff;
}
Maximp = duplicateImage(ip);
ipMax = Maximp.getProcessor();
RankFilters rf = new RankFilters();
rf.rank(ipMax, radius, rf.MAX); // Maximum
// Maximp.show();
Minimp = duplicateImage(ip);
ipMin = Minimp.getProcessor();
rf.rank(ipMin, radius, rf.MIN); // Minimum
// Minimp.show();
byte[] pixels = (byte[]) ip.getPixels();
byte[] max = (byte[]) ipMax.getPixels();
byte[] min = (byte[]) ipMin.getPixels();
for (int i = 0; i < pixels.length; i++) {
pixels[i] =
((int) (pixels[i] & 0xff) > (int) (((max[i] & 0xff) + (min[i] & 0xff)) / 2) - c_value)
? object
: backg;
}
// imp.updateAndDraw();
return;
}
/**
* 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};
}
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 int setup(String arg, ImagePlus imp) {
this.arg = arg;
IJ.register(Binary.class);
doOptions = arg.equals("options");
if (doOptions) {
if (imp == null) return NO_IMAGE_REQUIRED; // options dialog does not need a (suitable) image
ImageProcessor ip = imp.getProcessor();
if (!(ip instanceof ByteProcessor)) return NO_IMAGE_REQUIRED;
if (!((ByteProcessor) ip).isBinary()) return NO_IMAGE_REQUIRED;
}
return flags;
}
void lineWidth() {
int width = (int) IJ.getNumber("Line Width:", Line.getWidth());
if (width == IJ.CANCELED) return;
Line.setWidth(width);
LineWidthAdjuster.update();
ImagePlus imp = WindowManager.getCurrentImage();
if (imp != null && imp.isProcessor()) {
ImageProcessor ip = imp.getProcessor();
ip.setLineWidth(Line.getWidth());
Roi roi = imp.getRoi();
if (roi != null && roi.isLine()) imp.draw();
}
}
void Mean(ImagePlus imp, int radius, double par1, double par2, boolean doIwhite) {
// See: Image Processing Learning Resourches HIPR2
// http://homepages.inf.ed.ac.uk/rbf/HIPR2/adpthrsh.htm
ImagePlus Meanimp;
ImageProcessor ip = imp.getProcessor(), ipMean;
int c_value = 0;
byte object;
byte backg;
if (par1 != 0) {
IJ.log("Mean: changed c_value from :" + c_value + " to:" + par1);
c_value = (int) par1;
}
if (doIwhite) {
object = (byte) 0xff;
backg = (byte) 0;
} else {
object = (byte) 0;
backg = (byte) 0xff;
}
Meanimp = duplicateImage(ip);
ImageConverter ic = new ImageConverter(Meanimp);
ic.convertToGray32();
ipMean = Meanimp.getProcessor();
RankFilters rf = new RankFilters();
rf.rank(ipMean, radius, rf.MEAN); // Mean
// Meanimp.show();
byte[] pixels = (byte[]) ip.getPixels();
float[] mean = (float[]) ipMean.getPixels();
for (int i = 0; i < pixels.length; i++)
pixels[i] = ((int) (pixels[i] & 0xff) > (int) (mean[i] - c_value)) ? object : backg;
// imp.updateAndDraw();
return;
}
void setStackDisplayRange(ImagePlus imp) {
ImageStack stack = imp.getStack();
double min = Double.MAX_VALUE;
double max = -Double.MAX_VALUE;
int n = stack.getSize();
for (int i = 1; i <= n; i++) {
if (!silentMode) IJ.showStatus("Calculating stack min and max: " + i + "/" + n);
ImageProcessor ip = stack.getProcessor(i);
ip.resetMinAndMax();
if (ip.getMin() < min) min = ip.getMin();
if (ip.getMax() > max) max = ip.getMax();
}
imp.getProcessor().setMinAndMax(min, max);
imp.updateAndDraw();
}
// at the very end - show output image (if the is a separate one)
private void showOutput() {
if (interrupted) return;
if (outStack != null) {
outImp = new ImagePlus(TITLE_PREFIX[processType] + imp.getShortTitle(), outStack);
int[] d = imp.getDimensions();
outImp.setDimensions(d[2], d[3], d[4]);
for (int i = 1; i <= imp.getStackSize(); i++)
outStack.setSliceLabel(imp.getStack().getSliceLabel(i), i);
}
if (outImageType != BYTE_OVERWRITE) {
ImageProcessor ip = outImp.getProcessor();
if (!Prefs.blackBackground) ip.invertLut();
ip.resetMinAndMax();
outImp.show();
}
}
/** Opens a stack of images. */
ImagePlus openStack(ColorModel cm, boolean show) {
ImageStack stack = new ImageStack(fi.width, fi.height, cm);
long skip = fi.getOffset();
Object pixels;
try {
ImageReader reader = new ImageReader(fi);
InputStream is = createInputStream(fi);
if (is == null) return null;
IJ.resetEscape();
for (int i = 1; i <= fi.nImages; i++) {
if (!silentMode) IJ.showStatus("Reading: " + i + "/" + fi.nImages);
if (IJ.escapePressed()) {
IJ.beep();
IJ.showProgress(1.0);
silentMode = false;
return null;
}
pixels = reader.readPixels(is, skip);
if (pixels == null) break;
stack.addSlice(null, pixels);
skip = fi.gapBetweenImages;
if (!silentMode) IJ.showProgress(i, fi.nImages);
}
is.close();
} catch (Exception e) {
IJ.log("" + e);
} catch (OutOfMemoryError e) {
IJ.outOfMemory(fi.fileName);
stack.trim();
}
if (!silentMode) IJ.showProgress(1.0);
if (stack.getSize() == 0) return null;
if (fi.sliceLabels != null && fi.sliceLabels.length <= stack.getSize()) {
for (int i = 0; i < fi.sliceLabels.length; i++) stack.setSliceLabel(fi.sliceLabels[i], i + 1);
}
ImagePlus imp = new ImagePlus(fi.fileName, stack);
if (fi.info != null) imp.setProperty("Info", fi.info);
if (show) imp.show();
imp.setFileInfo(fi);
setCalibration(imp);
ImageProcessor ip = imp.getProcessor();
if (ip.getMin() == ip.getMax()) // find stack min and max if first slice is blank
setStackDisplayRange(imp);
if (!silentMode) IJ.showProgress(1.0);
silentMode = false;
return imp;
}
void setHistogram(ImagePlus imp, int j) {
ImageProcessor ip = imp.getProcessor();
ImageStatistics stats = ImageStatistics.getStatistics(ip, AREA + MODE, null);
int maxCount2 = 0;
histogram = stats.histogram;
for (int i = 0; i < stats.nBins; i++)
if ((histogram[i] > maxCount2) && (i != stats.mode)) maxCount2 = histogram[i];
hmax = stats.maxCount;
if ((hmax > (maxCount2 * 1.5)) && (maxCount2 != 0)) { // GL 1.5 was 2
hmax = (int) (maxCount2 * 1.1); // GL 1.1 was 1.5
histogram[stats.mode] = hmax;
}
os = null;
ColorModel cm = ip.getColorModel();
if (!(cm instanceof IndexColorModel)) return;
IndexColorModel icm = (IndexColorModel) cm;
int mapSize = icm.getMapSize();
if (mapSize != 256) return;
byte[] r = new byte[256];
byte[] g = new byte[256];
byte[] b = new byte[256];
icm.getReds(r);
icm.getGreens(g);
icm.getBlues(b);
hColors = new Color[256];
if (isRGB) {
if (j == 0) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(i & 255, 0 & 255, 0 & 255);
} else if (j == 1) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(0 & 255, i & 255, 0 & 255);
} else if (j == 2) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(0 & 255, 0 & 255, i & 255);
}
} else {
if (j == 0) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(r[i] & 255, g[i] & 255, b[i] & 255);
} else if (j == 1) {
for (int i = 0; i < 256; i++)
// hColors[i] = new Color(127-i/2&255, 127+i/2&255, 127-i/2&255);
hColors[i] = new Color(192 - i / 4 & 255, 192 + i / 4 & 255, 192 - i / 4 & 255);
} else if (j == 2) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(i & 255, i & 255, 0 & 255);
}
}
}
public void run(String arg) {
imp = IJ.getImage();
Roi roi = imp.getRoi();
if (roi != null && !roi.isArea()) imp.killRoi(); // ignore any line selection
ImageProcessor ip = imp.getProcessor();
if (!showDialog(ip)) return;
if (ip.getWidth() > 1 && ip.getHeight() > 1) ip.setInterpolate(interpolate);
else ip.setInterpolate(false);
ip.setBackgroundValue(bgValue);
imp.startTiming();
try {
if (newWindow && imp.getStackSize() > 1 && processStack) createNewStack(imp, ip);
else scale(ip);
} catch (OutOfMemoryError o) {
IJ.outOfMemory("Scale");
}
IJ.showProgress(1.0);
}
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);
}
void createSelectionFromMask(ImagePlus imp) {
ImageProcessor ip = imp.getProcessor();
if (ip.getMinThreshold() != ImageProcessor.NO_THRESHOLD) {
IJ.runPlugIn("ij.plugin.filter.ThresholdToSelection", "");
return;
}
if (!ip.isBinary()) {
IJ.error(
"Create Selection",
"This command creates a composite selection from\n"
+ "a mask (8-bit binary image with white background)\n"
+ "or from an image that has been thresholded using\n"
+ "the Image>Adjust>Threshold tool. The current\n"
+ "image is not a mask and has not been thresholded.");
return;
}
int threshold = ip.isInvertedLut() ? 255 : 0;
ip.setThreshold(threshold, threshold, ImageProcessor.NO_LUT_UPDATE);
IJ.runPlugIn("ij.plugin.filter.ThresholdToSelection", "");
}
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;
}
public void run(String arg) {
ImagePlus imp = WindowManager.getCurrentImage();
if (imp == null) {
IJ.noImage();
return;
}
if (imp.getStackSize() > 1) {
IJ.error("This command requires a montage");
return;
}
GenericDialog gd = new GenericDialog("Stack Maker");
gd.addNumericField("Images_per_row: ", w, 0);
gd.addNumericField("Images_per_column: ", h, 0);
gd.addNumericField("Border width: ", b, 0);
gd.showDialog();
if (gd.wasCanceled()) return;
w = (int) gd.getNextNumber();
h = (int) gd.getNextNumber();
b = (int) gd.getNextNumber();
ImageStack stack = makeStack(imp.getProcessor(), w, h, b);
new ImagePlus("Stack", stack).show();
}
/** Splits the specified image into separate channels. */
public static ImagePlus[] split(ImagePlus imp) {
if (imp.getType() == ImagePlus.COLOR_RGB) {
ImageStack[] stacks = splitRGB(imp.getStack(), true);
ImagePlus[] images = new ImagePlus[3];
images[0] = new ImagePlus("red", stacks[0]);
images[1] = new ImagePlus("green", stacks[1]);
images[2] = new ImagePlus("blue", stacks[2]);
return images;
}
int width = imp.getWidth();
int height = imp.getHeight();
int channels = imp.getNChannels();
int slices = imp.getNSlices();
int frames = imp.getNFrames();
int bitDepth = imp.getBitDepth();
int size = slices * frames;
Vector images = new Vector();
HyperStackReducer reducer = new HyperStackReducer(imp);
for (int c = 1; c <= channels; c++) {
ImageStack stack2 = new ImageStack(width, height, size); // create empty stack
stack2.setPixels(
imp.getProcessor().getPixels(), 1); // can't create ImagePlus will null 1st image
ImagePlus imp2 = new ImagePlus("C" + c + "-" + imp.getTitle(), stack2);
stack2.setPixels(null, 1);
imp.setPosition(c, 1, 1);
imp2.setDimensions(1, slices, frames);
imp2.setCalibration(imp.getCalibration());
reducer.reduce(imp2);
if (imp.isComposite() && ((CompositeImage) imp).getMode() == IJ.GRAYSCALE)
IJ.run(imp2, "Grays", "");
if (imp2.getNDimensions() > 3) imp2.setOpenAsHyperStack(true);
images.add(imp2);
}
ImagePlus[] array = new ImagePlus[images.size()];
return (ImagePlus[]) images.toArray(array);
}
/** Opens the image. Displays it if 'show' is true. Returns an ImagePlus object if successful. */
public ImagePlus open(boolean show) {
ImagePlus imp = null;
Object pixels;
ProgressBar pb = null;
ImageProcessor ip;
ColorModel cm = createColorModel(fi);
if (fi.nImages > 1) {
return openStack(cm, show);
}
switch (fi.fileType) {
case FileInfo.GRAY8:
case FileInfo.COLOR8:
case FileInfo.BITMAP:
pixels = readPixels(fi);
if (pixels == null) return null;
ip = new ByteProcessor(width, height, (byte[]) pixels, cm);
imp = new ImagePlus(fi.fileName, ip);
break;
case FileInfo.GRAY16_SIGNED:
case FileInfo.GRAY16_UNSIGNED:
case FileInfo.GRAY12_UNSIGNED:
pixels = readPixels(fi);
if (pixels == null) return null;
ip = new ShortProcessor(width, height, (short[]) pixels, cm);
imp = new ImagePlus(fi.fileName, ip);
break;
case FileInfo.GRAY32_INT:
case FileInfo.GRAY32_UNSIGNED:
case FileInfo.GRAY32_FLOAT:
case FileInfo.GRAY24_UNSIGNED:
case FileInfo.GRAY64_FLOAT:
pixels = readPixels(fi);
if (pixels == null) return null;
ip = new FloatProcessor(width, height, (float[]) pixels, cm);
imp = new ImagePlus(fi.fileName, ip);
break;
case FileInfo.RGB:
case FileInfo.BGR:
case FileInfo.ARGB:
case FileInfo.ABGR:
case FileInfo.BARG:
case FileInfo.RGB_PLANAR:
pixels = readPixels(fi);
if (pixels == null) return null;
ip = new ColorProcessor(width, height, (int[]) pixels);
imp = new ImagePlus(fi.fileName, ip);
break;
case FileInfo.RGB48:
case FileInfo.RGB48_PLANAR:
boolean planar = fi.fileType == FileInfo.RGB48_PLANAR;
Object[] pixelArray = (Object[]) readPixels(fi);
if (pixelArray == null) return null;
ImageStack stack = new ImageStack(width, height);
stack.addSlice("Red", pixelArray[0]);
stack.addSlice("Green", pixelArray[1]);
stack.addSlice("Blue", pixelArray[2]);
imp = new ImagePlus(fi.fileName, stack);
imp.setDimensions(3, 1, 1);
if (planar) imp.getProcessor().resetMinAndMax();
imp.setFileInfo(fi);
int mode = CompositeImage.COMPOSITE;
if (fi.description != null) {
if (fi.description.indexOf("mode=color") != -1) mode = CompositeImage.COLOR;
else if (fi.description.indexOf("mode=gray") != -1) mode = CompositeImage.GRAYSCALE;
}
imp = new CompositeImage(imp, mode);
if (!planar && fi.displayRanges == null) {
for (int c = 1; c <= 3; c++) {
imp.setPosition(c, 1, 1);
imp.setDisplayRange(minValue, maxValue);
}
imp.setPosition(1, 1, 1);
}
break;
}
imp.setFileInfo(fi);
setCalibration(imp);
if (fi.info != null) imp.setProperty("Info", fi.info);
if (fi.sliceLabels != null && fi.sliceLabels.length == 1 && fi.sliceLabels[0] != null)
imp.setProperty("Label", fi.sliceLabels[0]);
if (show) imp.show();
return imp;
}
void setCalibration(ImagePlus imp) {
if (fi.fileType == FileInfo.GRAY16_SIGNED) {
if (IJ.debugMode) IJ.log("16-bit signed");
double[] coeff = new double[2];
coeff[0] = -32768.0;
coeff[1] = 1.0;
imp.getLocalCalibration().setFunction(Calibration.STRAIGHT_LINE, coeff, "gray value");
}
Properties props = decodeDescriptionString(fi);
Calibration cal = imp.getCalibration();
boolean calibrated = false;
if (fi.pixelWidth > 0.0 && fi.unit != null) {
cal.pixelWidth = fi.pixelWidth;
cal.pixelHeight = fi.pixelHeight;
cal.pixelDepth = fi.pixelDepth;
cal.setUnit(fi.unit);
calibrated = true;
}
if (fi.valueUnit != null) {
int f = fi.calibrationFunction;
if ((f >= Calibration.STRAIGHT_LINE && f <= Calibration.RODBARD2 && fi.coefficients != null)
|| f == Calibration.UNCALIBRATED_OD) {
boolean zeroClip = props != null && props.getProperty("zeroclip", "false").equals("true");
cal.setFunction(f, fi.coefficients, fi.valueUnit, zeroClip);
calibrated = true;
}
}
if (calibrated) checkForCalibrationConflict(imp, cal);
if (fi.frameInterval != 0.0) cal.frameInterval = fi.frameInterval;
if (props == null) return;
cal.xOrigin = getDouble(props, "xorigin");
cal.yOrigin = getDouble(props, "yorigin");
cal.zOrigin = getDouble(props, "zorigin");
cal.info = props.getProperty("info");
cal.fps = getDouble(props, "fps");
cal.loop = getBoolean(props, "loop");
cal.frameInterval = getDouble(props, "finterval");
cal.setTimeUnit(props.getProperty("tunit", "sec"));
double displayMin = getDouble(props, "min");
double displayMax = getDouble(props, "max");
if (!(displayMin == 0.0 && displayMax == 0.0)) {
int type = imp.getType();
ImageProcessor ip = imp.getProcessor();
if (type == ImagePlus.GRAY8 || type == ImagePlus.COLOR_256)
ip.setMinAndMax(displayMin, displayMax);
else if (type == ImagePlus.GRAY16 || type == ImagePlus.GRAY32) {
if (ip.getMin() != displayMin || ip.getMax() != displayMax)
ip.setMinAndMax(displayMin, displayMax);
}
}
int stackSize = imp.getStackSize();
if (stackSize > 1) {
int channels = (int) getDouble(props, "channels");
int slices = (int) getDouble(props, "slices");
int frames = (int) getDouble(props, "frames");
if (channels == 0) channels = 1;
if (slices == 0) slices = 1;
if (frames == 0) frames = 1;
// IJ.log("setCalibration: "+channels+" "+slices+" "+frames);
if (channels * slices * frames == stackSize) {
imp.setDimensions(channels, slices, frames);
if (getBoolean(props, "hyperstack")) imp.setOpenAsHyperStack(true);
}
}
}
/** Restores original disk or network version of image. */
public void revertToSaved(ImagePlus imp) {
Image img;
ProgressBar pb = IJ.getInstance().getProgressBar();
ImageProcessor ip;
String path = fi.directory + fi.fileName;
if (fi.fileFormat == fi.GIF_OR_JPG) {
// restore gif or jpg
img = Toolkit.getDefaultToolkit().createImage(path);
imp.setImage(img);
if (imp.getType() == ImagePlus.COLOR_RGB) Opener.convertGrayJpegTo8Bits(imp);
return;
}
if (fi.fileFormat == fi.DICOM) {
// restore DICOM
ImagePlus imp2 = (ImagePlus) IJ.runPlugIn("ij.plugin.DICOM", path);
if (imp2 != null) imp.setProcessor(null, imp2.getProcessor());
return;
}
if (fi.fileFormat == fi.BMP) {
// restore BMP
ImagePlus imp2 = (ImagePlus) IJ.runPlugIn("ij.plugin.BMP_Reader", path);
if (imp2 != null) imp.setProcessor(null, imp2.getProcessor());
return;
}
if (fi.fileFormat == fi.PGM) {
// restore PGM
ImagePlus imp2 = (ImagePlus) IJ.runPlugIn("ij.plugin.PGM_Reader", path);
if (imp2 != null) imp.setProcessor(null, imp2.getProcessor());
return;
}
if (fi.fileFormat == fi.ZIP_ARCHIVE) {
// restore ".zip" file
ImagePlus imp2 = (new Opener()).openZip(path);
if (imp2 != null) imp.setProcessor(null, imp2.getProcessor());
return;
}
// restore PNG or another image opened using ImageIO
if (fi.fileFormat == fi.IMAGEIO) {
ImagePlus imp2 = (new Opener()).openUsingImageIO(path);
if (imp2 != null) imp.setProcessor(null, imp2.getProcessor());
return;
}
if (fi.nImages > 1) return;
ColorModel cm;
if (fi.url == null || fi.url.equals("")) IJ.showStatus("Loading: " + path);
else IJ.showStatus("Loading: " + fi.url + fi.fileName);
Object pixels = readPixels(fi);
if (pixels == null) return;
cm = createColorModel(fi);
switch (fi.fileType) {
case FileInfo.GRAY8:
case FileInfo.COLOR8:
case FileInfo.BITMAP:
ip = new ByteProcessor(width, height, (byte[]) pixels, cm);
imp.setProcessor(null, ip);
break;
case FileInfo.GRAY16_SIGNED:
case FileInfo.GRAY16_UNSIGNED:
case FileInfo.GRAY12_UNSIGNED:
ip = new ShortProcessor(width, height, (short[]) pixels, cm);
imp.setProcessor(null, ip);
break;
case FileInfo.GRAY32_INT:
case FileInfo.GRAY32_FLOAT:
ip = new FloatProcessor(width, height, (float[]) pixels, cm);
imp.setProcessor(null, ip);
break;
case FileInfo.RGB:
case FileInfo.BGR:
case FileInfo.ARGB:
case FileInfo.ABGR:
case FileInfo.RGB_PLANAR:
img =
Toolkit.getDefaultToolkit()
.createImage(new MemoryImageSource(width, height, (int[]) pixels, 0, width));
imp.setImage(img);
break;
}
}
/*
if selection is closed shape, create a circle with the same area and centroid, otherwise use<br>
the Pratt method to fit a circle to the points that define the line or multi-point selection.<br>
Reference: Pratt V., Direct least-squares fitting of algebraic surfaces", Computer Graphics, Vol. 21, pages 145-152 (1987).<br>
Original code: Nikolai Chernov's MATLAB script for Newton-based Pratt fit.<br>
(http://www.math.uab.edu/~chernov/cl/MATLABcircle.html)<br>
Java version: https://github.com/mdoube/BoneJ/blob/master/src/org/doube/geometry/FitCircle.java<br>
@authors Nikolai Chernov, Michael Doube, Ved Sharma
*/
void fitCircle(ImagePlus imp) {
Roi roi = imp.getRoi();
if (roi == null) {
noRoi("Fit Circle");
return;
}
if (roi.isArea()) { // create circle with the same area and centroid
ImageProcessor ip = imp.getProcessor();
ip.setRoi(roi);
ImageStatistics stats =
ImageStatistics.getStatistics(ip, Measurements.AREA + Measurements.CENTROID, null);
double r = Math.sqrt(stats.pixelCount / Math.PI);
imp.killRoi();
int d = (int) Math.round(2.0 * r);
IJ.makeOval(
(int) Math.round(stats.xCentroid - r), (int) Math.round(stats.yCentroid - r), d, d);
return;
}
Polygon poly = roi.getPolygon();
int n = poly.npoints;
int[] x = poly.xpoints;
int[] y = poly.ypoints;
if (n < 3) {
IJ.error("Fit Circle", "At least 3 points are required to fit a circle.");
return;
}
// calculate point centroid
double sumx = 0, sumy = 0;
for (int i = 0; i < n; i++) {
sumx = sumx + poly.xpoints[i];
sumy = sumy + poly.ypoints[i];
}
double meanx = sumx / n;
double meany = sumy / n;
// calculate moments
double[] X = new double[n], Y = new double[n];
double Mxx = 0, Myy = 0, Mxy = 0, Mxz = 0, Myz = 0, Mzz = 0;
for (int i = 0; i < n; i++) {
X[i] = x[i] - meanx;
Y[i] = y[i] - meany;
double Zi = X[i] * X[i] + Y[i] * Y[i];
Mxy = Mxy + X[i] * Y[i];
Mxx = Mxx + X[i] * X[i];
Myy = Myy + Y[i] * Y[i];
Mxz = Mxz + X[i] * Zi;
Myz = Myz + Y[i] * Zi;
Mzz = Mzz + Zi * Zi;
}
Mxx = Mxx / n;
Myy = Myy / n;
Mxy = Mxy / n;
Mxz = Mxz / n;
Myz = Myz / n;
Mzz = Mzz / n;
// calculate the coefficients of the characteristic polynomial
double Mz = Mxx + Myy;
double Cov_xy = Mxx * Myy - Mxy * Mxy;
double Mxz2 = Mxz * Mxz;
double Myz2 = Myz * Myz;
double A2 = 4 * Cov_xy - 3 * Mz * Mz - Mzz;
double A1 = Mzz * Mz + 4 * Cov_xy * Mz - Mxz2 - Myz2 - Mz * Mz * Mz;
double A0 = Mxz2 * Myy + Myz2 * Mxx - Mzz * Cov_xy - 2 * Mxz * Myz * Mxy + Mz * Mz * Cov_xy;
double A22 = A2 + A2;
double epsilon = 1e-12;
double ynew = 1e+20;
int IterMax = 20;
double xnew = 0;
int iterations = 0;
// Newton's method starting at x=0
for (int iter = 1; iter <= IterMax; iter++) {
iterations = iter;
double yold = ynew;
ynew = A0 + xnew * (A1 + xnew * (A2 + 4. * xnew * xnew));
if (Math.abs(ynew) > Math.abs(yold)) {
if (IJ.debugMode) IJ.log("Fit Circle: wrong direction: |ynew| > |yold|");
xnew = 0;
break;
}
double Dy = A1 + xnew * (A22 + 16 * xnew * xnew);
double xold = xnew;
xnew = xold - ynew / Dy;
if (Math.abs((xnew - xold) / xnew) < epsilon) break;
if (iter >= IterMax) {
if (IJ.debugMode) IJ.log("Fit Circle: will not converge");
xnew = 0;
}
if (xnew < 0) {
if (IJ.debugMode) IJ.log("Fit Circle: negative root: x = " + xnew);
xnew = 0;
}
}
if (IJ.debugMode)
IJ.log("Fit Circle: n=" + n + ", xnew=" + IJ.d2s(xnew, 2) + ", iterations=" + iterations);
// calculate the circle parameters
double DET = xnew * xnew - xnew * Mz + Cov_xy;
double CenterX = (Mxz * (Myy - xnew) - Myz * Mxy) / (2 * DET);
double CenterY = (Myz * (Mxx - xnew) - Mxz * Mxy) / (2 * DET);
double radius = Math.sqrt(CenterX * CenterX + CenterY * CenterY + Mz + 2 * xnew);
if (Double.isNaN(radius)) {
IJ.error("Fit Circle", "Points are collinear.");
return;
}
CenterX = CenterX + meanx;
CenterY = CenterY + meany;
imp.killRoi();
IJ.makeOval(
(int) Math.round(CenterX - radius),
(int) Math.round(CenterY - radius),
(int) Math.round(2 * radius),
(int) Math.round(2 * radius));
}
