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imagej-elphel
Commit b3e36d25 authored by Andrey Filippov's avatar Andrey Filippov
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Working on generating re-sampling arrays for rotation/scaling 2D 

correlation
parent 182ed7f3
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Showing with 211 additions and 6 deletions
src/main/java/com/elphel/imagej/tileprocessor/Correlation2d.java
View file @ b3e36d25
......@@ -370,7 +370,7 @@ public class Correlation2d {
public double getCombDisp() {return mcorr_comb_disp;}
public void generateResample( // should be called before
public void generateResampleOld( // should be called before
final int mcorr_comb_width, // combined correlation tile width
final int mcorr_comb_height, // combined correlation tile full height
final int mcorr_comb_offset, // combined correlation tile height offset: 0 - centered (-height/2 to height/2), height/2 - only positive (0 to height)
......@@ -419,6 +419,10 @@ public class Correlation2d {
HashSet<Integer> contrib_set = new HashSet<Integer>();
Iterator<Integer> contrib_itr;
for (int num_pair = ai.getAndIncrement(); num_pair < corr_pairs.length; num_pair = ai.getAndIncrement()) {
if (num_pair == 62) {
System.out.println("num_pair="+num_pair);
System.out.println("num_pair="+num_pair);
}
if (corr_pairs[num_pair]) {
resample_indices[num_pair] = new int [mcorr_comb_width * mcorr_comb_height][];
resample_weights[num_pair] = new double [mcorr_comb_width * mcorr_comb_height][];
......@@ -444,13 +448,26 @@ public class Correlation2d {
int ix = j - mcorr_comb_width/2;
Arrays.fill(contrib, 0.0);
contrib_set.clear();
for (int idy = 0; idy <= 2*SUB_SAMPLE; idy++) {
if ((num_pair == 62) && (i==7) && (j==7)) {
System.out.println("num_pair="+num_pair+", i="+i+", j="+j);
System.out.println("num_pair="+num_pair+", i="+i+", j="+j);
}
for (int idy = 0; idy < weights_size; idy++) {
mxy.set(1, 0, iy+ (idy - SUB_SAMPLE + 1) * ksub); //idy == (SUB_SAMPLE -1) - no fractional pixel
for (int idx = 0; idx <= 2*SUB_SAMPLE; idx++) {
for (int idx = 0; idx < weights_size; idx++) {
mxy.set(0, 0, ix+ (idx - SUB_SAMPLE + 1) * ksub); // idy == (SUB_SAMPLE -1) - no fractional pixel
double [] pxy = toPair.times(mxy).getColumnPackedCopy();
int ipx = (int) Math.round(pxy[0]+transform_size -1);
int ipy = (int) Math.round(pxy[1]+transform_size -1);
// int ipx = (int) Math.round(pxy[0]+transform_size -1);
// int ipy = (int) Math.round(pxy[1]+transform_size -1);
// round symmetrically (away from zero)
double dpx = pxy[0]+transform_size -1;
double dpy = pxy[1]+transform_size -1;
int ipx = (int) Math.round(Math.abs(dpx));
int ipy = (int) Math.round(Math.abs(dpy));
if (dpx < 0) ipx = -ipx;
if (dpy < 0) ipy = -ipy;
if ((ipx >= 0) && (ipy >= 0) && (ipx < corr_size) && (ipy < corr_size)) {
int indx_src = ipy * corr_size + ipx;
contrib_set.add(indx_src);
......@@ -468,6 +485,7 @@ public class Correlation2d {
int indx_src = contrib_itr.next();
resample_indices[num_pair][indx][contrib_num] = indx_src;
resample_weights[num_pair][indx][contrib_num] = contrib[indx_src];
contrib_num++;
}
}
}
......@@ -482,7 +500,194 @@ public class Correlation2d {
}
ImageDtt.startAndJoin(threads);
}
public void generateResample( // should be called before
final int mcorr_comb_width, // combined correlation tile width
final int mcorr_comb_height, // combined correlation tile full height
final int mcorr_comb_offset, // combined correlation tile height offset: 0 - centered (-height/2 to height/2), height/2 - only positive (0 to height)
final double mcorr_comb_disp){ // Combined tile per-pixel disparity for baseline == side of a square
final double ignore_contrib = 0.001; // ignore contributors with weight below
this.mcorr_comb_width = mcorr_comb_width; // combined correlation tile width
this.mcorr_comb_height = mcorr_comb_height; // combined correlation tile full height
this.mcorr_comb_offset = mcorr_comb_offset; // combined correlation tile height offset: 0 - centered (-height/2 to height/2), height/2 - only positive (0 to height)
this.mcorr_comb_disp = mcorr_comb_disp; // Combined tile per-pixel disparity for baseline == side of a square
resample_indices = new int [corr_pairs.length][][];
resample_weights = new double [corr_pairs.length][][];
final double [][] four_corners = {{-1,-1},{1,-1},{-1, 1},{1, 1}};
// final int corr_size = 2 * transform_size - 1;
final int corr_center_offs = 2 * transform_size * (transform_size -1);
// final double [][][][] resample = new double [pair_start_end.length][mcorr_comb_width * mcorr_comb_height][][];
// use multithreading?
final Thread[] threads = ImageDtt.newThreadArray(THREADS_MAX);
final AtomicInteger ai = new AtomicInteger(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
public void run() {
double [] contrib = new double [corr_size*corr_size];
HashSet<Integer> contrib_set = new HashSet<Integer>();
Iterator<Integer> contrib_itr;
double [][] xy4acc = new double[4][2];
double [][] xy4pair = new double[4][2];
ArrayList<Integer> contrib_list = new ArrayList<Integer>();
ArrayList<Double> contrib_weights_list = new ArrayList<Double>();
for (int num_pair = ai.getAndIncrement(); num_pair < corr_pairs.length; num_pair = ai.getAndIncrement()) {
if (num_pair == 62) {
System.out.println("num_pair="+num_pair);
System.out.println("num_pair="+num_pair);
}
if (corr_pairs[num_pair]) {
resample_indices[num_pair] = new int [mcorr_comb_width * mcorr_comb_height][];
resample_weights[num_pair] = new double [mcorr_comb_width * mcorr_comb_height][];
// scale and angle
int istart = pair_start_end[num_pair][0];
int iend = pair_start_end[num_pair][1];
double cwrot = (((istart+iend) % numSensors) + (top_is_0 ? 0.0 : 0.5)) * Math.PI/numSensors; // +(top_is_0 ? 0.0 : 0.5)
if ((iend > istart) ^ ((iend + istart) <16)) {
cwrot += Math.PI;
}
double pl = 2 * Math.sin(Math.PI* pair_length[num_pair] / numSensors); // length for R=1
// scale - to get pair (source) radius from combo (destination) radius
double scale = pl/Math.sqrt(2.0)* mcorr_comb_disp; // Math.sqrt(2.0) - relative to side of a square - may be change later?
Matrix toPair = new Matrix(new double[][] {
{scale * Math.cos(cwrot), -scale*Math.sin(cwrot)},
{scale * Math.sin(cwrot), scale*Math.cos(cwrot)}});
Matrix fromPair = toPair.inverse();
Matrix mxy = new Matrix(2,1);
Matrix mpxy = new Matrix(2,1);
// 2 methods depending on scale
if (scale >= 1.0) { // pair grid is finer, than accumulated grid
for (int i = 0; i < mcorr_comb_height; i++) {
int iy = i + mcorr_comb_offset - mcorr_comb_height/2;
for (int j = 0; j < mcorr_comb_width; j++) {
int ix = j - mcorr_comb_width/2;
// convert +/- 1 pixel to pair
double minXPair = Double.NaN,minYPair = Double.NaN, maxXPair = Double.NaN, maxYPair = Double.NaN;
for (int d = 0; d < four_corners.length; d++) {
mxy.set(0, 0, ix + four_corners[d][0]);
mxy.set(1, 0, iy + four_corners[d][1]);
double [] xy_pair = toPair.times(mxy).getColumnPackedCopy();
if (d == 0) {
minXPair = xy_pair[0];
maxXPair = minXPair;
minYPair = xy_pair[1];
maxYPair = minYPair;
} else {
minXPair = Math.min(minXPair,xy_pair[0]);
minYPair = Math.min(minYPair,xy_pair[1]);
maxXPair = Math.max(maxXPair,xy_pair[0]);
maxYPair = Math.max(maxYPair,xy_pair[1]);
}
}
int iMinXPair = (int) Math.floor(minXPair);
int iMinYPair = (int) Math.floor(minYPair);
int iMaxXPair = (int) Math.ceil (maxXPair);
int iMaxYPair = (int) Math.ceil (maxYPair);
// limit by available data
if (iMinXPair < (1 - transform_size)) iMinXPair = 1- transform_size;
if (iMaxXPair > (transform_size - 1)) iMaxXPair = transform_size -1;
if (iMinYPair < (1 - transform_size)) iMinYPair = 1- transform_size;
if (iMaxYPair > (transform_size - 1)) iMaxYPair = transform_size -1;
// corr_center_offs , corr_len
if ((iMaxXPair >= iMinXPair) && (iMaxYPair >= iMinYPair)) {
contrib_list.clear();
contrib_weights_list.clear();
double sumw = 0.0;
for (int ipy= iMinYPair; ipy <= iMaxYPair; ipy ++) {
mpxy.set(1, 0, ipy);
for (int ipx= iMinXPair; ipx <= iMaxXPair; ipx ++) {
mpxy.set(0, 0, ipx);
double [] xy_acc = fromPair.times(mpxy).getColumnPackedCopy();
// did it get to square of influence?
if ( (xy_acc[0] > (ix - 1)) &&
(xy_acc[0] < (ix + 1)) &&
(xy_acc[1] > (iy - 1)) &&
(xy_acc[1] < (iy + 1))) {
double w = Math.cos(0.5 * Math.PI * (xy_acc[0] - ix)) *
Math.cos(0.5 * Math.PI * (xy_acc[1] - iy));
w *= w;
if (w >= ignore_contrib) {
int pair_indx = ipy * corr_size + ipx;
contrib_list.add(pair_indx);
sumw += w;
contrib_weights_list.add(w);
}
}
}
}
if (sumw > 0) {
// normalize and store contributions
int indx = i * mcorr_comb_width + j;
int ncontrib = contrib_list.size();
resample_indices[num_pair][indx] = new int [ncontrib];
resample_weights[num_pair][indx] = new double [ncontrib];
for (int icontrib = 0; icontrib < ncontrib; icontrib++) {
resample_indices[num_pair][indx][icontrib] = contrib_list.get(icontrib);
resample_weights[num_pair][indx][icontrib] = contrib_weights_list.get(icontrib) / sumw;
}
}
}
}
}
} else { // if (scale >= 1.0) { // pair grid is coarser, than accumulated grid
for (int i = 0; i < mcorr_comb_height; i++) {
int iy = i + mcorr_comb_offset - mcorr_comb_height/2;
for (int j = 0; j < mcorr_comb_width; j++) {
int ix = j - mcorr_comb_width/2;
mxy.set(0, 0, ix);
mxy.set(1, 0, iy);
double [] xy_pair = toPair.times(mxy).getColumnPackedCopy();
// find 4 corners in the pair array
if ( (xy_pair[0] >= (1 - transform_size)) &&
(xy_pair[0] <= (transform_size - 1)) &&
(xy_pair[1] >= (1 - transform_size)) &&
(xy_pair[1] <= (transform_size - 1))) {
contrib_list.clear();
contrib_weights_list.clear();
int px0 = (int) Math.floor(xy_pair[0]);
int py0 = (int) Math.floor(xy_pair[1]);
double sumw = 0.0;
double wx0 = Math.cos(0.5*Math.PI*(xy_pair[0] - Math.floor(xy_pair[0])));
double wx1 = Math.cos(0.5*Math.PI*(Math.ceil(xy_pair[0]) - xy_pair[0]));
double wy0 = Math.cos(0.5*Math.PI*(xy_pair[1] - Math.floor(xy_pair[1])));
double wy1 = Math.cos(0.5*Math.PI*(Math.ceil(xy_pair[1]) - xy_pair[1]));
double [] wxy = {wx0*wy0, wx1*wy0, wx0*wy1, wx1*wy1};
int [] pair_ind = {
py0 * corr_size + px0,
py0 * corr_size + px0 + 1,
(py0 + 1) * corr_size + px0,
(py0 + 1) * corr_size + px0 + 1};
for (int d = 0; d < wxy.length; d++) {
double w = wxy[d]*wxy[d];
if (w >= ignore_contrib) {
contrib_list.add(pair_ind[d]);
contrib_weights_list.add(w);
sumw += w;
}
}
if (sumw > 0) {
// normalize and store contributions
int indx = i * mcorr_comb_width + j;
int ncontrib = contrib_list.size();
resample_indices[num_pair][indx] = new int [ncontrib];
resample_weights[num_pair][indx] = new double [ncontrib];
for (int icontrib = 0; icontrib < ncontrib; icontrib++) {
resample_indices[num_pair][indx][icontrib] = contrib_list.get(icontrib);
resample_weights[num_pair][indx][icontrib] = contrib_weights_list.get(icontrib) / sumw;
}
}
}
}
}
}
}
}
}
};
}
ImageDtt.startAndJoin(threads);
}
public Correlation2d ( // USED in lwir
int numSensors,
ImageDttParameters imgdtt_params,
......
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