/**
* Saito-Toriwaki algorithm for Euclidian Distance Transformation. Direct application of Algorithm
* 1. Bob Dougherty 8/8/2006
*
* <ul>
* <li>Version S1A: lower memory usage.
* <li>Version S1A.1 A fixed indexing bug for 666-bin data set
* <li>Version S1A.2 Aug. 9, 2006. Changed noResult value.
* <li>Version S1B Aug. 9, 2006. Faster.
* <li>Version S1B.1 Sept. 6, 2006. Changed comments.
* <li>Version S1C Oct. 1, 2006. Option for inverse case. <br>
* Fixed inverse behavior in y and z directions.
* <li>Version D July 30, 2007. Multithread processing for step 2.
* </ul>
*
* <p>This version assumes the input stack is already in memory, 8-bit, and outputs to a new
* 32-bit stack. Versions that are more stingy with memory may be forthcoming.
*
* @param imp 8-bit (binary) ImagePlus
*/
private float[][] geometryToDistanceMap(ImagePlus imp, boolean inv) {
final int w = imp.getWidth();
final int h = imp.getHeight();
final int d = imp.getStackSize();
int nThreads = Runtime.getRuntime().availableProcessors();
// Create references to input data
ImageStack stack = imp.getStack();
byte[][] data = new byte[d][];
for (int k = 0; k < d; k++) data[k] = (byte[]) stack.getPixels(k + 1);
// Create 32 bit floating point stack for output, s. Will also use it
// for g in Transformation 1.
float[][] s = new float[d][];
for (int k = 0; k < d; k++) {
ImageProcessor ipk = new FloatProcessor(w, h);
s[k] = (float[]) ipk.getPixels();
}
float[] sk;
// Transformation 1. Use s to store g.
IJ.showStatus("EDT transformation 1/3");
Step1Thread[] s1t = new Step1Thread[nThreads];
for (int thread = 0; thread < nThreads; thread++) {
s1t[thread] = new Step1Thread(thread, nThreads, w, h, d, inv, s, data);
s1t[thread].start();
}
try {
for (int thread = 0; thread < nThreads; thread++) {
s1t[thread].join();
}
} catch (InterruptedException ie) {
IJ.error("A thread was interrupted in step 1 .");
}
// Transformation 2. g (in s) -> h (in s)
IJ.showStatus("EDT transformation 2/3");
Step2Thread[] s2t = new Step2Thread[nThreads];
for (int thread = 0; thread < nThreads; thread++) {
s2t[thread] = new Step2Thread(thread, nThreads, w, h, d, s);
s2t[thread].start();
}
try {
for (int thread = 0; thread < nThreads; thread++) {
s2t[thread].join();
}
} catch (InterruptedException ie) {
IJ.error("A thread was interrupted in step 2 .");
}
// Transformation 3. h (in s) -> s
IJ.showStatus("EDT transformation 3/3");
Step3Thread[] s3t = new Step3Thread[nThreads];
for (int thread = 0; thread < nThreads; thread++) {
s3t[thread] = new Step3Thread(thread, nThreads, w, h, d, inv, s, data);
s3t[thread].start();
}
try {
for (int thread = 0; thread < nThreads; thread++) {
s3t[thread].join();
}
} catch (InterruptedException ie) {
IJ.error("A thread was interrupted in step 3 .");
}
// Find the largest distance for scaling
// Also fill in the background values.
float distMax = 0;
final int wh = w * h;
float dist;
for (int k = 0; k < d; k++) {
sk = s[k];
for (int ind = 0; ind < wh; ind++) {
if (((data[k][ind] & 255) < 128) ^ inv) {
sk[ind] = 0;
} else {
dist = (float) Math.sqrt(sk[ind]);
sk[ind] = dist;
distMax = (dist > distMax) ? dist : distMax;
}
}
}
IJ.showProgress(1.0);
IJ.showStatus("Done");
return s;
}
/**
* DistanceRidgetoLocalThickness
*
* <p>Input: Distance Ridge (32-bit stack) (Output from Distance Ridge.java) Output: Local
* Thickness. Overwrites the input.
*
* <ul>
* <li>Version 1: September 6, 2006.
* <li>Version 2: September 25, 2006. Fixed several bugs that resulted in non-symmetrical output
* from symmetrical input.
* <li>Version 2.1 Oct. 1, 2006. Fixed a rounding error that caused some points to be missed.
* <li>Version 3 July 31, 2007. Parallel processing version.
* <li>Version 3.1 Multiplies the output by 2 to conform with the definition of local thickness
* </ul>
*
* @param imp
*/
private void distanceRidgetoLocalThickness(ImagePlus imp, float[][] s) {
final int w = imp.getWidth();
final int h = imp.getHeight();
final int d = imp.getStackSize();
float[] sk;
// Count the distance ridge points on each slice
int[] nRidge = new int[d];
int ind, nr, iR;
IJ.showStatus("Local Thickness: scanning stack ");
for (int k = 0; k < d; k++) {
sk = s[k];
nr = 0;
for (int j = 0; j < h; j++) {
final int wj = w * j;
for (int i = 0; i < w; i++) {
ind = i + wj;
if (sk[ind] > 0) nr++;
}
}
nRidge[k] = nr;
}
int[][] iRidge = new int[d][];
int[][] jRidge = new int[d][];
float[][] rRidge = new float[d][];
// Pull out the distance ridge points
int[] iRidgeK, jRidgeK;
float[] rRidgeK;
float sMax = 0;
for (int k = 0; k < d; k++) {
nr = nRidge[k];
iRidge[k] = new int[nr];
jRidge[k] = new int[nr];
rRidge[k] = new float[nr];
sk = s[k];
iRidgeK = iRidge[k];
jRidgeK = jRidge[k];
rRidgeK = rRidge[k];
iR = 0;
for (int j = 0; j < h; j++) {
final int wj = w * j;
for (int i = 0; i < w; i++) {
ind = i + wj;
if (sk[ind] > 0) {;
iRidgeK[iR] = i;
jRidgeK[iR] = j;
rRidgeK[iR++] = sk[ind];
if (sk[ind] > sMax) sMax = sk[ind];
sk[ind] = 0;
}
}
}
}
int nThreads = Runtime.getRuntime().availableProcessors();
final Object[] resources = new Object[d]; // For synchronization
for (int k = 0; k < d; k++) {
resources[k] = new Object();
}
LTThread[] ltt = new LTThread[nThreads];
for (int thread = 0; thread < nThreads; thread++) {
ltt[thread] =
new LTThread(thread, nThreads, w, h, d, nRidge, s, iRidge, jRidge, rRidge, resources);
ltt[thread].start();
}
try {
for (int thread = 0; thread < nThreads; thread++) {
ltt[thread].join();
}
} catch (InterruptedException ie) {
IJ.error("A thread was interrupted .");
}
// Fix the square values and apply factor of 2
IJ.showStatus("Local Thickness: square root ");
for (int k = 0; k < d; k++) {
sk = s[k];
for (int j = 0; j < h; j++) {
final int wj = w * j;
for (int i = 0; i < w; i++) {
ind = i + wj;
sk[ind] = (float) (2 * Math.sqrt(sk[ind]));
}
}
}
IJ.showStatus("Local Thickness complete");
return;
}
/**
* Create a Thread[] array as large as the number of processors available. From Stephan
* Preibisch's Multithreading.java class. See:
* http://repo.or.cz/w/trakem2.git?a=blob;f=mpi/fruitfly/general/MultiThreading.java;hb=HEAD
*/
private Thread[] newThreadArray() {
int n_cpus = Runtime.getRuntime().availableProcessors();
return new Thread[n_cpus];
}