/**
* Creates a new FloatProcessor using the specified ImageProcessor. Set 'cm' to null to use the
* default grayscale LUT.
*/
public SerializableFloatProcessor(ImageProcessor imageProcessor) {
imageProcessor = imageProcessor.duplicate();
FloatProcessor floatProcessor = imageProcessor.toFloat(0, null);
this.width = floatProcessor.getWidth();
this.height = floatProcessor.getHeight();
this.pixels = (float[]) floatProcessor.getPixels();
this.cm = floatProcessor.getColorModel();
resetRoi();
if (pixels != null) findMinAndMax();
}
boolean eraseOutsideRoi(ImageProcessor ip, Rectangle r, ImageProcessor mask) {
int width = ip.getWidth();
int height = ip.getHeight();
ip.setRoi(r);
if (excludeEdgeParticles && polygon != null) {
ImageStatistics stats = ImageStatistics.getStatistics(ip, MIN_MAX, null);
if (fillColor >= stats.min && fillColor <= stats.max) {
double replaceColor = level1 - 1.0;
if (replaceColor < 0.0 || replaceColor == fillColor) {
replaceColor = level2 + 1.0;
int maxColor = imageType == BYTE ? 255 : 65535;
if (replaceColor > maxColor || replaceColor == fillColor) {
IJ.error("Particle Analyzer", "Unable to remove edge particles");
return false;
}
}
for (int y = minY; y < maxY; y++) {
for (int x = minX; x < maxX; x++) {
int v = ip.getPixel(x, y);
if (v == fillColor) ip.putPixel(x, y, (int) replaceColor);
}
}
}
}
ip.setValue(fillColor);
if (mask != null) {
mask = mask.duplicate();
mask.invert();
ip.fill(mask);
}
ip.setRoi(0, 0, r.x, height);
ip.fill();
ip.setRoi(r.x, 0, r.width, r.y);
ip.fill();
ip.setRoi(r.x, r.y + r.height, r.width, height - (r.y + r.height));
ip.fill();
ip.setRoi(r.x + r.width, 0, width - (r.x + r.width), height);
ip.fill();
ip.resetRoi();
// IJ.log("erase: "+fillColor+" "+level1+" "+level2+" "+excludeEdgeParticles);
// (new ImagePlus("ip2", ip.duplicate())).show();
return true;
}
@Override
public Grid2D applyToolToImage(Grid2D imageProcessor) {
FloatProcessor imp = new FloatProcessor(imageProcessor.getWidth(), imageProcessor.getHeight());
imp.setPixels(imageProcessor.getBuffer());
if (!initBead) initializeBead();
ImageProcessor imp1 = imp.duplicate(); // original
double[][] beadMean3D = config.getBeadMeanPosition3D(); // [beadNo][x,y,z]
double[] uv = new double[1];
SimpleMatrix pMatrix = config.getGeometry().getProjectionMatrix(imageIndex).computeP();
// [projection #][bead #][u, v, state[0: initial, 1: registered, 2: updated by hough searching]]
double[][][] beadPosition2D = config.getBeadPosition2D();
int noBeadRegistered = 0;
double[][] xy1 = new double[WeightBearingBeadPositionBuilder.beadNo][2]; // original
double[][] xy2 =
new double[WeightBearingBeadPositionBuilder.beadNo]
[2]; // warped (mapped to the mean), control points, reference
double[][] xy1_hat = new double[WeightBearingBeadPositionBuilder.beadNo][2]; // original
double[][] xy2_hat = new double[WeightBearingBeadPositionBuilder.beadNo][2]; // original
// double distanceReferenceToCurrentBead = 0;
for (int i = WeightBearingBeadPositionBuilder.currentBeadNo; i >= 0; i--) {
if (beadMean3D[i][0] != 0
|| beadMean3D[i][1] != 0
|| beadMean3D[i][2] != 0) { // assume bead 3d is registered.
uv = compute2DCoordinates(beadMean3D[i], pMatrix);
// find bead location if registered by txt: state 1
if (beadPosition2D[imageIndex][i][2] == 1) {
noBeadRegistered++;
if (isDisplay) {
imp1.setValue(2);
imp1.drawLine(
(int) Math.round(beadPosition2D[imageIndex][i][0] - 10),
(int) Math.round(beadPosition2D[imageIndex][i][1] - 10),
(int) Math.round(beadPosition2D[imageIndex][i][0] + 10),
(int) Math.round(beadPosition2D[imageIndex][i][1] + 10));
imp1.drawLine(
(int) Math.round(beadPosition2D[imageIndex][i][0] - 10),
(int) Math.round(beadPosition2D[imageIndex][i][1] + 10),
(int) Math.round(beadPosition2D[imageIndex][i][0] + 10),
(int) Math.round(beadPosition2D[imageIndex][i][1] - 10));
imp1.drawString(
"Bead " + i + " (state:" + (int) beadPosition2D[imageIndex][i][2] + ")",
(int) beadPosition2D[imageIndex][i][0],
(int) beadPosition2D[imageIndex][i][1] - 10);
}
xy1[noBeadRegistered - 1][0] = beadPosition2D[imageIndex][i][0];
xy1[noBeadRegistered - 1][1] = beadPosition2D[imageIndex][i][1];
xy2[noBeadRegistered - 1][0] = uv[0];
xy2[noBeadRegistered - 1][1] = uv[1];
} else if (imageIndex != 0
&& imageIndex != config.getGeometry().getNumProjectionMatrices() - 1) {
if (beadPosition2D[imageIndex - 1][i][2] == 1
&& beadPosition2D[imageIndex + 1][i][2] == 1) {
noBeadRegistered++;
double xMean =
(beadPosition2D[imageIndex - 1][i][0] + beadPosition2D[imageIndex - 1][i][0]) / 2;
double yMean =
(beadPosition2D[imageIndex + 1][i][1] + beadPosition2D[imageIndex + 1][i][1]) / 2;
if (isDisplay) {
imp1.setValue(2);
imp1.drawLine(
(int) Math.round(xMean - 10),
(int) Math.round(yMean - 10),
(int) Math.round(xMean + 10),
(int) Math.round(yMean + 10));
imp1.drawLine(
(int) Math.round(xMean - 10),
(int) Math.round(yMean + 10),
(int) Math.round(xMean + 10),
(int) Math.round(yMean - 10));
imp1.drawString("Bead " + i + " (state:" + "M)", (int) xMean, (int) yMean - 10);
}
xy1[noBeadRegistered - 1][0] = xMean;
xy1[noBeadRegistered - 1][1] = yMean;
xy2[noBeadRegistered - 1][0] = uv[0];
xy2[noBeadRegistered - 1][1] = uv[1];
}
}
// mean projected bead
// imp1.drawLine((int) Math.round(uv[0]-10), (int) Math.round(uv[1]), (int)
// Math.round(uv[0]+10), (int) Math.round(uv[1]));
// imp1.drawLine((int) Math.round(uv[0]), (int) Math.round(uv[1]-10), (int)
// Math.round(uv[0]), (int) Math.round(uv[1]+10));
}
}
if (isDisplay) {
for (int x = 0; x < config.getGeometry().getDetectorWidth(); x += 50)
imp1.drawLine(x, 0, x, config.getGeometry().getDetectorHeight());
for (int y = 0; y < config.getGeometry().getDetectorHeight(); y += 50)
imp1.drawLine(0, y, config.getGeometry().getDetectorWidth(), y);
}
if (isCornerIncluded) {
xy1[noBeadRegistered + 0][0] = 0;
xy1[noBeadRegistered + 0][1] = 0;
xy2[noBeadRegistered + 0][0] = 0;
xy2[noBeadRegistered + 0][1] = 0;
xy1[noBeadRegistered + 1][0] = 0;
xy1[noBeadRegistered + 1][1] = config.getGeometry().getDetectorHeight();
xy2[noBeadRegistered + 1][0] = 0;
xy2[noBeadRegistered + 1][1] = config.getGeometry().getDetectorHeight();
xy1[noBeadRegistered + 2][0] = config.getGeometry().getDetectorWidth();
xy1[noBeadRegistered + 2][1] = 0;
xy2[noBeadRegistered + 2][0] = config.getGeometry().getDetectorWidth();
xy2[noBeadRegistered + 2][1] = 0;
xy1[noBeadRegistered + 3][0] = config.getGeometry().getDetectorWidth();
xy1[noBeadRegistered + 3][1] = config.getGeometry().getDetectorHeight();
xy2[noBeadRegistered + 3][0] = config.getGeometry().getDetectorWidth();
xy2[noBeadRegistered + 3][1] = config.getGeometry().getDetectorHeight();
noBeadRegistered = noBeadRegistered + 4;
}
boolean fScaling = true;
double minX = Double.MAX_VALUE;
double maxX = 0;
double minY = Double.MAX_VALUE;
double maxY = 0;
double c = 0;
if (fScaling) { // ----- scaling to reduce condition # of A matrix
for (int i = 0; i < noBeadRegistered; i++) {
minX = Math.min(minX, xy1[i][0]);
maxX = Math.max(maxX, xy1[i][0]);
minY = Math.min(minY, xy1[i][1]);
maxY = Math.max(maxY, xy1[i][1]);
}
c = Math.max(maxX - minX, maxY - minY);
for (int i = 0; i < noBeadRegistered; i++) {
xy1_hat[i][0] = (xy1[i][0] - minX) / c;
xy1_hat[i][1] = (xy1[i][1] - minY) / c;
xy2_hat[i][0] = (xy2[i][0] - minX) / c;
xy2_hat[i][1] = (xy2[i][1] - minY) / c;
}
} else {
xy1_hat = xy1;
xy2_hat = xy2;
}
ImageProcessor imp2 = imp1.duplicate(); // warped
/*
* A*x = b
* Matrix A = (n + 3) * (n + 3);
* n (noBeadRegistered + 4): # of control points + 4 corner points (assume corner points are static)
*/
int n = noBeadRegistered + 3;
SimpleMatrix A = new SimpleMatrix(n, n);
SimpleVector x_x = new SimpleVector(n);
SimpleVector x_y = new SimpleVector(n);
SimpleVector b_x = new SimpleVector(n);
SimpleVector b_y = new SimpleVector(n);
double rij = 0;
double valA = 0;
double valb_x = 0;
double valb_y = 0;
// Matrix L formation
// alpha: mean of distances between control points' xy-projections) is a constant only present
// on the diagonal of K
// lambda: TPS smoothing regularization coefficient
double alpha = 0.0;
double lambda = 1.6; // 1.6
for (int i = 0; i < noBeadRegistered; i++) { // i= # of row
for (int j = i; j < noBeadRegistered; j++) { // j= # of column
alpha +=
Math.sqrt(
Math.pow(xy2_hat[i][0] - xy2_hat[j][0], 2)
+ Math.pow(xy2_hat[i][1] - xy2_hat[j][1], 2));
}
}
alpha = alpha / Math.pow(noBeadRegistered, 2);
for (int i = 0; i < n; i++) { // i= # of row
for (int j = i; j < n; j++) { // j= # of column
if (i < 3 && j < 3) valA = 0;
else if (i >= 3 && j >= 3 && i == j) {
valA = Math.pow(alpha, 2) * lambda;
// valA = lambda;
if (imageIndex < 10)
System.out.println("Regularization = " + valA + ", lambda= " + lambda);
} else if (i == 0 && j >= 0) valA = 1;
else if (i == 1 && j >= 3) valA = xy1_hat[j - 3][0];
else if (i == 2 && j >= 3) valA = xy1_hat[j - 3][1];
else {
rij =
Math.pow(xy1_hat[j - 3][0] - xy1_hat[i - 3][0], 2)
+ Math.pow(xy1_hat[j - 3][1] - xy1_hat[i - 3][1], 2);
if (rij == 0) valA = 0;
else valA = rij * Math.log(rij);
}
A.setElementValue(i, j, valA);
A.setElementValue(j, i, valA);
}
if (i < 3) {
valb_x = 0;
valb_y = 0;
} else {
// valb_x = xy2_hat[i-3][0]-xy1_hat[i-3][0];
// valb_y = xy2_hat[i-3][1]-xy1_hat[i-3][1];
valb_x = xy2[i - 3][0] - xy1[i - 3][0];
valb_y = xy2[i - 3][1] - xy1[i - 3][1];
// if (imageIndex > 150 && imageIndex < 170)
// System.out.println("Idx" + imageIndex + ",Elevation" + (i-3) + ": " + valb_x + "---"
// + valb_y);
}
b_x.setElementValue(i, valb_x);
b_y.setElementValue(i, valb_y);
}
// System.out.println("A condition number=" + A.conditionNumber(MatrixNormType.MAT_NORM_L1));
// System.out.println("A condition number=" + A.conditionNumber(MatrixNormType.MAT_NORM_LINF));
x_x = Solvers.solveLinearSysytemOfEquations(A, b_x);
x_y = Solvers.solveLinearSysytemOfEquations(A, b_y);
if (fScaling) {
// ----- pixel space coefficients a, b scaling back
double tmpA0 =
x_x.getElement(0) - x_x.getElement(1) * (minX / c) - x_x.getElement(2) * (minY / c);
for (int j = 0; j < noBeadRegistered; j++) {
tmpA0 -=
Math.log(c)
* 2
* x_x.getElement(j + 3)
* (Math.pow(xy1_hat[j][0], 2) + Math.pow(xy1_hat[j][1], 2));
}
x_x.setElementValue(0, tmpA0);
tmpA0 = x_y.getElement(0) - x_y.getElement(1) * (minX / c) - x_y.getElement(2) * (minY / c);
for (int j = 0; j < noBeadRegistered; j++) {
tmpA0 -=
Math.log(c)
* 2
* x_y.getElement(j + 3)
* (Math.pow(xy1_hat[j][0], 2) + Math.pow(xy1_hat[j][1], 2));
}
x_y.setElementValue(0, tmpA0);
x_x.setElementValue(1, x_x.getElement(1) / c);
x_y.setElementValue(1, x_y.getElement(1) / c);
x_x.setElementValue(2, x_x.getElement(2) / c);
x_y.setElementValue(2, x_y.getElement(2) / c);
for (int i = 3; i < n; i++) {
x_x.setElementValue(i, x_x.getElement(i) / Math.pow(c, 2));
x_y.setElementValue(i, x_y.getElement(i) / Math.pow(c, 2));
}
// ----- pixel space coefficients a, b scaling back end
}
double devU = 0;
double devV = 0;
// Do warping
// if (imageIndex == 0) {
for (int y = 0; y < config.getGeometry().getDetectorHeight(); y++) {
// for (int y=252; y<253; y++) {
for (int x = 0; x < config.getGeometry().getDetectorWidth(); x++) {
// for (int x=606; x<607; x++) {
devU = x_x.getElement(0) + x_x.getElement(1) * x + x_x.getElement(2) * y;
devV = x_y.getElement(0) + x_y.getElement(1) * x + x_y.getElement(2) * y;
for (int i = 0; i < noBeadRegistered; i++) {
rij = Math.pow(xy1[i][0] - x, 2) + Math.pow(xy1[i][1] - y, 2);
if (rij > 0) {
devU += x_x.getElement(i + 3) * rij * Math.log(rij);
devV += x_y.getElement(i + 3) * rij * Math.log(rij);
}
}
// devU = 0;
// devV = 0;
imp2.setf(x, y, (float) imp1.getInterpolatedValue(x - devU, y - devV));
// System.out.println("x, y=" + x + ", " + y + "\t" + devU + ", " + devV);
// maxDevU = Math.max(maxDevU, devU);
// maxDevV = Math.max(maxDevV, devV);
}
}
// Error estimate after transformation
// for (int i=0; i<= WeightBearingBeadPositionBuilder.currentBeadNo; i++){
//
// if (beadMean3D[i][0] != 0 || beadMean3D[i][1] != 0 || beadMean3D[i][2] != 0){ // assume
// bead 3d is registered.
//
// // find bead location if registered by txt: state 1
// if (beadPosition2D[imageIndex][i][2] == 1){
//
// // Projected Reference
// uv = compute2DCoordinates(beadMean3D[i], pMatrix);
// double x = uv[0];
// double y = uv[1];
// // bead detected position in 2d
// // Transform to 2D coordinates, time variant position
// //beadPosition2D[imageIndex][i][0];
// //beadPosition2D[imageIndex][i][1];
//
// devU = x_x.getElement(0) + x_x.getElement(1)*x + x_x.getElement(2)*y;
// devV = x_y.getElement(0) + x_y.getElement(1)*x + x_y.getElement(2)*y;
// for (int j=0; j<noBeadRegistered; j++){
// rij = Math.pow(xy1[j][0]-x, 2) + Math.pow(xy1[j][1]-y, 2);
// if (rij > 0) {
// devU += x_x.getElement(j+3)*rij*Math.log(rij);
// devV += x_y.getElement(j+3)*rij*Math.log(rij);
// }
// }
//
// distanceReferenceToCurrentBead +=
// Math.sqrt(Math.pow(uv[0]-(beadPosition2D[imageIndex][i][0]+devU),
// 2)+Math.pow(uv[1]-(beadPosition2D[imageIndex][i][1]+devV), 2));
//
// }
// }
// }
// System.out.println("Euclidean distance\t" + imageIndex + "\t" +
// distanceReferenceToCurrentBead/noBeadRegistered);
// }
if (isDisplay) {
for (int i = WeightBearingBeadPositionBuilder.currentBeadNo; i >= 0; i--) {
if (beadMean3D[i][0] != 0
|| beadMean3D[i][1] != 0
|| beadMean3D[i][2] != 0) { // assume bead 3d is registered.
uv = compute2DCoordinates(beadMean3D[i], pMatrix);
imp2.setValue(2);
// mean projected bead
imp2.drawLine(
(int) Math.round(uv[0] - 10),
(int) Math.round(uv[1]),
(int) Math.round(uv[0] + 10),
(int) Math.round(uv[1]));
imp2.drawLine(
(int) Math.round(uv[0]),
(int) Math.round(uv[1] - 10),
(int) Math.round(uv[0]),
(int) Math.round(uv[1] + 10));
}
}
}
Grid2D result = new Grid2D((float[]) imp2.getPixels(), imp2.getWidth(), imp2.getHeight());
return result;
}
// Particle finding routine based on spots enhancement with
// 2D PSF Gaussian approximated convolution/backgrounds subtraction, thresholding
// and particle filtering
void detectParticles(
ImageProcessor ip, SMLDialog fdg, int nFrame, Overlay SpotsPositions_, Roi RoiActive_) {
int nThreshold;
FloatProcessor dupip = null; // duplicate of image
ImageProcessor dushort; // duplicate of image
ByteProcessor dubyte = null; // tresholded image
TypeConverter tc;
dupip = (FloatProcessor) ip.duplicate().convertToFloat();
SMLblur1Direction(
dupip, fdg.dPSFsigma * 0.5, 0.0002, true, (int) Math.ceil(5 * fdg.dPSFsigma * 0.5));
SMLblur1Direction(dupip, fdg.dPSFsigma * 0.5, 0.0002, false, 0);
// new ImagePlus("gassconvoluted", dupip.convertToFloat().duplicate()).show();
// low-pass filtering by gaussian blurring
// lowpassGauss.blurGaussian(dupip, fdg.dPSFsigma*0.5, fdg.dPSFsigma*0.5, 0.0002);
// convolution with gaussian PSF kernel
SMLconvolveFloat(dupip, fConKernel, fdg.nKernelSize, fdg.nKernelSize);
// new ImagePlus("convoluted", dupip.duplicate()).show();
tc = new TypeConverter(dupip, true);
dushort = tc.convertToShort();
// new ImagePlus("convoluted", dushort.duplicate()).show();
// thresholding
// old straightforward thresholding
// imgstat = ImageStatistics.getStatistics(dupip, 22, null); //6 means MEAN + STD_DEV, look at
// ij.measure.Measurements
// nThreshold = (int)(imgstat.mean + 3.0*imgstat.stdDev);
// new smart thresholding
nThreshold = getThreshold(dushort);
dushort.threshold(nThreshold);
// convert to byte
dubyte = (ByteProcessor) dushort.convertToByte(false);
// new ImagePlus("threshold", dubyte.duplicate()).show();
// morphological operations on thresholded image
// dubyte.dilate(2, 0);
// dubyte.erode(2, 0);
// cleaning up image a bit
if (fdg.nKernelSize > 3) {
dubyte.dilate();
// new ImagePlus("dilated", dubyte.duplicate()).show();
dubyte.erode();
// new ImagePlus("erosion", dubyte.duplicate()).show();
}
// dupip.invert();
labelParticles(
dubyte,
ip,
nFrame,
fdg.dPixelSize,
fdg.nAreaCut,
fdg.dPSFsigma,
SpotsPositions_,
fdg.bShowParticles,
RoiActive_); // , fdg.bIgnoreFP);//, fdg.dSymmetry/100);
}
/**
* 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;
}
/** 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
}
}
/**
* @param ip
* @param v
*/
public static void run(final ImageProcessor ip, final float v) {
final int w = ip.getWidth();
final int h = ip.getHeight();
final int wh = w * h;
final ImageProcessor ipTarget = ip.duplicate();
int numSaturatedPixels = 0;
do {
numSaturatedPixels = 0;
for (int i = 0; i < wh; ++i)
if (ip.getf(i) == v) {
++numSaturatedPixels;
final int y = i / w;
final int x = i % w;
float s = 0;
float n = 0;
if (y > 0) {
if (x > 0) {
final float tl = ip.getf(x - 1, y - 1);
if (tl != v) {
s += 0.5f * tl;
n += 0.5f;
}
}
final float t = ip.getf(x, y - 1);
if (t != v) {
s += t;
n += 1;
}
if (x < w - 1) {
final float tr = ip.getf(x + 1, y - 1);
if (tr != v) {
s += 0.5f * tr;
n += 0.5f;
}
}
}
if (x > 0) {
final float l = ip.getf(x - 1, y);
if (l != v) {
s += l;
n += 1;
}
}
if (x < w - 1) {
final float r = ip.getf(x + 1, y);
if (r != v) {
s += r;
n += 1;
}
}
if (y < h - 1) {
if (x > 0) {
final float bl = ip.getf(x - 1, y + 1);
if (bl != v) {
s += 0.5f * bl;
n += 0.5f;
}
}
final float b = ip.getf(x, y + 1);
if (b != v) {
s += b;
n += 1;
}
if (x < w - 1) {
final float br = ip.getf(x + 1, y + 1);
if (br != v) {
s += 0.5f * br;
n += 0.5f;
}
}
}
if (n > 0) ipTarget.setf(i, s / n);
}
ip.setPixels(ipTarget.getPixelsCopy());
} while (numSaturatedPixels > 0);
}
/*------------------------------------------------------------------*/
void doIt(ImageProcessor ip) {
int width = ip.getWidth();
int height = ip.getHeight();
double hLine[] = new double[width];
double vLine[] = new double[height];
if (!(ip.getPixels() instanceof float[])) {
throw new IllegalArgumentException("Float image required");
}
switch (operation) {
case GRADIENT_MAGNITUDE:
{
ImageProcessor h = ip.duplicate();
ImageProcessor v = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsH = (float[]) h.getPixels();
float[] floatPixelsV = (float[]) v.getPixels();
getHorizontalGradient(h, FLT_EPSILON);
getVerticalGradient(v, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] =
(float)
Math.sqrt(
floatPixelsH[k] * floatPixelsH[k] + floatPixelsV[k] * floatPixelsV[k]);
}
stepProgressBar();
}
}
break;
case GRADIENT_DIRECTION:
{
ImageProcessor h = ip.duplicate();
ImageProcessor v = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsH = (float[]) h.getPixels();
float[] floatPixelsV = (float[]) v.getPixels();
getHorizontalGradient(h, FLT_EPSILON);
getVerticalGradient(v, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] = (float) Math.atan2(floatPixelsH[k], floatPixelsV[k]);
}
stepProgressBar();
}
}
break;
case LAPLACIAN:
{
ImageProcessor hh = ip.duplicate();
ImageProcessor vv = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsHH = (float[]) hh.getPixels();
float[] floatPixelsVV = (float[]) vv.getPixels();
getHorizontalHessian(hh, FLT_EPSILON);
getVerticalHessian(vv, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] = (float) (floatPixelsHH[k] + floatPixelsVV[k]);
}
stepProgressBar();
}
}
break;
case LARGEST_HESSIAN:
{
ImageProcessor hh = ip.duplicate();
ImageProcessor vv = ip.duplicate();
ImageProcessor hv = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsHH = (float[]) hh.getPixels();
float[] floatPixelsVV = (float[]) vv.getPixels();
float[] floatPixelsHV = (float[]) hv.getPixels();
getHorizontalHessian(hh, FLT_EPSILON);
getVerticalHessian(vv, FLT_EPSILON);
getCrossHessian(hv, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] =
(float)
(0.5
* (floatPixelsHH[k]
+ floatPixelsVV[k]
+ Math.sqrt(
4.0 * floatPixelsHV[k] * floatPixelsHV[k]
+ (floatPixelsHH[k] - floatPixelsVV[k])
* (floatPixelsHH[k] - floatPixelsVV[k]))));
}
stepProgressBar();
}
}
break;
case SMALLEST_HESSIAN:
{
ImageProcessor hh = ip.duplicate();
ImageProcessor vv = ip.duplicate();
ImageProcessor hv = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsHH = (float[]) hh.getPixels();
float[] floatPixelsVV = (float[]) vv.getPixels();
float[] floatPixelsHV = (float[]) hv.getPixels();
getHorizontalHessian(hh, FLT_EPSILON);
getVerticalHessian(vv, FLT_EPSILON);
getCrossHessian(hv, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
floatPixels[k] =
(float)
(0.5
* (floatPixelsHH[k]
+ floatPixelsVV[k]
- Math.sqrt(
4.0 * floatPixelsHV[k] * floatPixelsHV[k]
+ (floatPixelsHH[k] - floatPixelsVV[k])
* (floatPixelsHH[k] - floatPixelsVV[k]))));
}
stepProgressBar();
}
}
break;
case HESSIAN_ORIENTATION:
{
ImageProcessor hh = ip.duplicate();
ImageProcessor vv = ip.duplicate();
ImageProcessor hv = ip.duplicate();
float[] floatPixels = (float[]) ip.getPixels();
float[] floatPixelsHH = (float[]) hh.getPixels();
float[] floatPixelsVV = (float[]) vv.getPixels();
float[] floatPixelsHV = (float[]) hv.getPixels();
getHorizontalHessian(hh, FLT_EPSILON);
getVerticalHessian(vv, FLT_EPSILON);
getCrossHessian(hv, FLT_EPSILON);
for (int y = 0, k = 0; (y < height); y++) {
for (int x = 0; (x < width); x++, k++) {
if (floatPixelsHV[k] < 0.0) {
floatPixels[k] =
(float)
(-0.5
* Math.acos(
(floatPixelsHH[k] - floatPixelsVV[k])
/ Math.sqrt(
4.0 * floatPixelsHV[k] * floatPixelsHV[k]
+ (floatPixelsHH[k] - floatPixelsVV[k])
* (floatPixelsHH[k] - floatPixelsVV[k]))));
} else {
floatPixels[k] =
(float)
(0.5
* Math.acos(
(floatPixelsHH[k] - floatPixelsVV[k])
/ Math.sqrt(
4.0 * floatPixelsHV[k] * floatPixelsHV[k]
+ (floatPixelsHH[k] - floatPixelsVV[k])
* (floatPixelsHH[k] - floatPixelsVV[k]))));
}
}
stepProgressBar();
}
}
break;
default:
throw new IllegalArgumentException("Invalid operation");
}
ip.resetMinAndMax();
imp.updateAndDraw();
} /* end doIt */
