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package ij.process;
import java.awt.*;
import ij.*;
import ij.process.*;
import ij.macro.Interpreter;
import ij.util.ArrayUtil;
import ij.plugin.Filters3D;
import java.util.concurrent.atomic.AtomicInteger;
/** This class processes stacks. */
public class StackProcessor {
public final static int FILTER_MEAN=Filters3D.MEAN, FILTER_MEDIAN=Filters3D.MEDIAN, FILTER_MIN=Filters3D.MIN,
FILTER_MAX=Filters3D.MAX, FILTER_VAR=Filters3D.VAR, FILTER_MAXLOCAL=Filters3D.MAXLOCAL;
private ImageStack stack;
private ImageProcessor ip;
int nSlices;
double xScale, yScale;
int[] table;
double fillValue;
float[] voxels;
/** Constructs a StackProcessor from a stack. */
public StackProcessor(ImageStack stack) {
this(stack, null);
}
/** Constructs a StackProcessor from a stack. 'ip' is the
processor that will be used to process the slices.
'ip' can be null when using crop(). */
public StackProcessor(ImageStack stack, ImageProcessor ip) {
this.stack = stack;
this.ip = ip;
nSlices = stack.size();
if (nSlices>1 && ip!=null)
ip.setProgressBar(null);
}
static final int FLIPH=0, FLIPV=1, SCALE=2, INVERT=3, APPLY_TABLE=4, SCALE_WITH_FILL=5;
void process(int command) {
String s = "";
ImageProcessor ip2 = stack.getProcessor(1);
switch (command) {
case FLIPH: case FLIPV: s="Flip: "; break;
case SCALE: s="Scale: "; break;
case SCALE_WITH_FILL: s="Scale: "; ip2.setBackgroundValue(fillValue); break;
case INVERT: s="Invert: "; break;
case APPLY_TABLE: s="Apply: "; break;
}
if (ip==null)
ip = ip2;
ip2.setRoi(this.ip.getRoi());
ip2.setInterpolate(this.ip.getInterpolate());
for (int i=1; i<=nSlices; i++) {
showStatus(s,i,nSlices);
ip2.setPixels(stack.getPixels(i));
if (nSlices==1 && i==1 && command==SCALE)
ip2.snapshot();
switch (command) {
case FLIPH: ip2.flipHorizontal(); break;
case FLIPV: ip2.flipVertical(); break;
case SCALE: case SCALE_WITH_FILL: ip2.scale(xScale, yScale); break;
case INVERT: ip2.invert(); break;
case APPLY_TABLE: ip2.applyTable(table); break;
}
IJ.showProgress((double)i/nSlices);
}
IJ.showProgress(1.0);
}
public void invert() {
process(INVERT);
}
public void flipHorizontal() {
process(FLIPH);
}
public void flipVertical() {
process(FLIPV);
}
public void applyTable(int[] table) {
this.table = table;
process(APPLY_TABLE);
}
public void scale(double xScale, double yScale) {
this.xScale = xScale;
this.yScale = yScale;
process(SCALE);
}
public void scale(double xScale, double yScale, double fillValue) {
this.xScale = xScale;
this.yScale = yScale;
this.fillValue = fillValue;
process(SCALE_WITH_FILL);
}
/** Creates a new stack with dimensions 'newWidth' x 'newHeight'.
To reduce memory requirements, the orginal stack is deleted
as the new stack is created. */
public ImageStack resize(int newWidth, int newHeight) {
return resize(newWidth, newHeight, false);
}
public ImageStack resize(int newWidth, int newHeight, boolean averageWhenDownsizing) {
ImageStack stack2 = new ImageStack(newWidth, newHeight);
ImageProcessor ip2;
Rectangle roi = ip!=null?ip.getRoi():null;
if (ip==null)
ip = stack.getProcessor(1).duplicate();
try {
for (int i=1; i<=nSlices; i++) {
showStatus("Resize: ",i,nSlices);
ip.setPixels(stack.getPixels(1));
String label = stack.getSliceLabel(1);
stack.deleteSlice(1);
ip2 = ip.resize(newWidth, newHeight, averageWhenDownsizing);
if (ip2!=null)
stack2.addSlice(label, ip2);
IJ.showProgress((double)i/nSlices);
}
IJ.showProgress(1.0);
} catch(OutOfMemoryError o) {
while(stack.size()>1)
stack.deleteLastSlice();
IJ.outOfMemory("StackProcessor.resize");
IJ.showProgress(1.0);
}
return stack2;
}
/** Crops the stack to the specified rectangle. */
public ImageStack crop(int x, int y, int width, int height) {
ImageStack stack2 = new ImageStack(width, height);
ImageProcessor ip2;
for (int i=1; i<=nSlices; i++) {
ImageProcessor ip1 = stack.getProcessor(1);
ip1.setRoi(x, y, width, height);
String label = stack.getSliceLabel(1);
stack.deleteSlice(1);
ip2 = ip1.crop();
stack2.addSlice(label, ip2);
IJ.showProgress((double)i/nSlices);
}
IJ.showProgress(1.0);
return stack2;
}
ImageStack rotate90Degrees(boolean clockwise) {
ImageStack stack2 = new ImageStack(stack.getHeight(), stack.getWidth());
ImageProcessor ip2;
if (ip==null)
ip = stack.getProcessor(1).duplicate();
for (int i=1; i<=nSlices; i++) {
showStatus("Rotate: ",i,nSlices);
ip.setPixels(stack.getPixels(1));
String label = stack.getSliceLabel(1);
stack.deleteSlice(1);
if (clockwise)
ip2 = ip.rotateRight();
else
ip2 = ip.rotateLeft();
if (ip2!=null)
stack2.addSlice(label, ip2);
if (!Interpreter.isBatchMode())
IJ.showProgress((double)i/nSlices);
}
if (!Interpreter.isBatchMode())
IJ.showProgress(1.0);
return stack2;
}
public ImageStack rotateRight() {
return rotate90Degrees(true);
}
public ImageStack rotateLeft() {
return rotate90Degrees(false);
}
public void copyBits(ImageProcessor src, int xloc, int yloc, int mode) {
copyBits(src, null, xloc, yloc, mode);
}
public void copyBits(ImageStack src, int xloc, int yloc, int mode) {
copyBits(null, src, xloc, yloc, mode);
}
private void copyBits(ImageProcessor srcIp, ImageStack srcStack, int xloc, int yloc, int mode) {
int inc = nSlices/20;
if (inc<1) inc = 1;
boolean stackSource = srcIp==null;
for (int i=1; i<=nSlices; i++) {
if (stackSource)
srcIp = srcStack.getProcessor(i);
ImageProcessor dstIp = stack.getProcessor(i);
dstIp.copyBits(srcIp, xloc, yloc, mode);
if ((i%inc) == 0) IJ.showProgress((double)i/nSlices);
}
IJ.showProgress(1.0);
}
void showStatus(String s, int n, int total) {
IJ.showStatus(s+n+"/"+total);
}
/**
* Thomas Boudier Create a kernel neighorhood as an ellipsoid
*
* @param radx Radius x of the ellipsoid
* @param rady Radius x of the ellipsoid
* @param radz Radius x of the ellipsoid
* @return The kernel as an array
*/
private int[] createKernelEllipsoid(float radx, float rady, float radz) {
int vx = (int) Math.ceil(radx);
int vy = (int) Math.ceil(rady);
int vz = (int) Math.ceil(radz);
int[] ker = new int[(2 * vx + 1) * (2 * vy + 1) * (2 * vz + 1)];
double dist;
double rx2 = radx * radx;
double ry2 = rady * rady;
double rz2 = radz * radz;
if (rx2 != 0) {
rx2 = 1.0 / rx2;
} else {
rx2 = 0;
}
if (ry2 != 0) {
ry2 = 1.0 / ry2;
} else {
ry2 = 0;
}
if (rz2 != 0) {
rz2 = 1.0 / rz2;
} else {
rz2 = 0;
}
int idx = 0;
for (int k = -vz; k <= vz; k++) {
for (int j = -vy; j <= vy; j++) {
for (int i = -vx; i <= vx; i++) {
dist = ((double) (i * i)) * rx2 + ((double) (j * j)) * ry2 + ((double) (k * k)) * rz2;
if (dist <= 1.0) {
ker[idx] = 1;
} else {
ker[idx] = 0;
}
idx++;
}
}
}
return ker;
}
/**
* 3D filter using threads
*
* @param out
* @param radx Radius of mean filter in x
* @param rady Radius of mean filter in y
* @param radz Radius of mean filter in z
* @param zmin
* @param zmax
* @param filter
*/
public void filter3D(ImageStack out, float radx, float rady, float radz, int zmin, int zmax, int filter) {
int[] ker = this.createKernelEllipsoid(radx, rady, radz);
int nb = 0;
for (int i=0; i<ker.length; i++)
nb += ker[i];
if (zmin<0)
zmin = 0;
if (zmax>stack.size())
zmax = stack.size();
int sizex = stack.getWidth();
int sizey = stack.getHeight();
double value;
for (int z=zmin; z<zmax; z++) {
if (zmin==0) IJ.showProgress(z+1, zmax);
for (int y=0; y<sizey; y++) {
for (int x=0; x<sizex; x++) {
ArrayUtil tab = getNeighborhood(ker, nb, x, y, z, radx, rady, radz);
switch (filter) {
case FILTER_MEAN:
out.setVoxel(x, y, z, tab.getMean()); break;
case FILTER_MEDIAN:
out.setVoxel(x, y, z, tab.medianSort()); break;
case FILTER_MIN:
out.setVoxel(x, y, z, tab.getMinimum()); break;
case FILTER_MAX:
out.setVoxel(x, y, z, tab.getMaximum()); break;
case FILTER_VAR:
out.setVoxel(x, y, z, tab.getVariance()); break;
case FILTER_MAXLOCAL:
value = stack.getVoxel(x, y, z);
if (tab.isMaximum(value))
out.setVoxel(x, y, z, value);
else
out.setVoxel(x, y, z, 0);
break;
} //switch
} //x
} //y
} //z
}
/*
private ArrayUtil getNeighborhood(int[] ker, int nbval, int x, int y, int z, float radx, float rady, float radz) {
int vx = (int)Math.ceil(radx);
int vy = (int)Math.ceil(rady);
int vz = (int)Math.ceil(radz);
int x0=x-vx, y0=y-vy, z0=z-vz;
int w=vx*2, h=vy*2, d=vz*2;
if (x0<0 || x0+w>stack.getWidth() || y0<0 || y0+h>stack.getHeight() || z0<0 || z0+d>stack.size())
return getEdgeNeighborhood(ker, nbval, x, y, z, radx, rady, radz);
voxels = stack.getVoxels(x0, y0, z0, w, h, d, voxels);
return new ArrayUtil(voxels);
}
*/
/**
* Gets the neighboring attribute of the Image3D with a kernel as a array
*
* @param ker The kernel array (>0 ok)
* @param nbval The number of non-zero values
* @param x Coordinate x of the pixel
* @param y Coordinate y of the pixel
* @param z Coordinate z of the pixel
* @param radx Radius x of the neighboring
* @param radz Radius y of the neighboring
* @param rady Radius z of the neighboring
* @return The values of the nieghbor pixels inside an array
*/
private ArrayUtil getNeighborhood(int[] ker, int nbval, int x, int y, int z, float radx, float rady, float radz) {
ArrayUtil pix = new ArrayUtil(nbval);
int vx = (int) Math.ceil(radx);
int vy = (int) Math.ceil(rady);
int vz = (int) Math.ceil(radz);
int index = 0;
int c = 0;
int sizex = stack.getWidth();
int sizey = stack.getHeight();
int sizez = stack.size();
for (int k = z - vz; k <= z + vz; k++) {
for (int j = y - vy; j <= y + vy; j++) {
for (int i = x - vx; i <= x + vx; i++) {
if (ker[c]>0 && i>=0 && j>=0 && k>=0 && i<sizex && j<sizey && k<sizez) {
pix.putValue(index, (float)stack.getVoxel(i, j, k));
index++;
}
c++;
}
}
}
pix.setSize(index);
return pix;
}
}
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