Commit 6346b15e authored by Andrey Filippov's avatar Andrey Filippov

updated ImageDttCPU:cltMeasureLazyEye() for variable number of sensors

parent 624db0c0
......@@ -317,6 +317,34 @@ public class ImageDttCPU {
static int TCORR_COMBO_VERT = 3; // combined correlation from 2 vertical pairs (0,1). Used to detect horizontal features
static String [] TCORR_TITLES = {"combo","sum","hor","vert"};
static int CORR_SEL_BIT_ALL = 0;
static int CORR_SEL_BIT_DIA = 1;
static int CORR_SEL_BIT_SQ = 2;
static int CORR_SEL_BIT_NEIB = 3;
static int CORR_SEL_BIT_HOR = 4;
static int CORR_SEL_BIT_VERT = 5;
public static int corrSelEncode(
boolean sel_all,
boolean sel_dia,
boolean sel_sq,
boolean sel_neib,
boolean sel_hor,
boolean sel_vert) {
return (sel_all ? (1 << CORR_SEL_BIT_ALL): 0) |
(sel_dia ? (1 << CORR_SEL_BIT_DIA): 0) |
(sel_sq ? (1 << CORR_SEL_BIT_SQ): 0) |
(sel_neib ? (1 << CORR_SEL_BIT_NEIB): 0) |
(sel_hor ? (1 << CORR_SEL_BIT_HOR): 0) |
(sel_vert ? (1 << CORR_SEL_BIT_VERT): 0);
}
public static boolean isCorrAll (int sel) { return ((sel >> CORR_SEL_BIT_ALL) & 1) != 0;}
public static boolean isCorrDia (int sel) { return ((sel >> CORR_SEL_BIT_DIA) & 1) != 0;}
public static boolean isCorrSq (int sel) { return ((sel >> CORR_SEL_BIT_SQ) & 1) != 0;}
public static boolean isCorrNeib(int sel) { return ((sel >> CORR_SEL_BIT_NEIB) & 1) != 0;}
public static boolean isCorrHor (int sel) { return ((sel >> CORR_SEL_BIT_HOR) & 1) != 0;}
public static boolean isCorrVert(int sel) { return ((sel >> CORR_SEL_BIT_VERT) & 1) != 0;}
private final boolean monochrome;
private final boolean lwir; // means that no sqrt correction
private final double scale_strengths; // scale all correlation strengths (to compensate for LPF sigma changes)
......@@ -2504,10 +2532,10 @@ public class ImageDttCPU {
// correlation results - final and partial
// When clt_mismatch is non-zero, no far objects extraction will be attempted
// 3 * numSensors
final double [][] clt_mismatch, // [3 * numSensors][tilesY * tilesX] // ***** transpose unapplied ***** ?. null - do not calculate
// final double [][] clt_mismatch, // [3 * numSensors][tilesY * tilesX] // ***** transpose unapplied ***** ?. null - do not calculate
// values in the "main" directions have disparity (*_CM) subtracted, in the perpendicular - as is
final double [][] disparity_map, // [8][tilesY][tilesX], only [6][] is needed on input or null - do not calculate
// final double [][] disparity_map, // [8][tilesY][tilesX], only [6][] is needed on input or null - do not calculate
// last 2 - contrast, avg/ "geometric average)
final int width,
......@@ -2527,10 +2555,7 @@ public class ImageDttCPU {
final double shiftY, // shift image vertically (positive - down)
final int tileStep, // process tileStep x tileStep cluster of tiles when adjusting lazy eye parameters
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 int mcorr_sel, // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
final int debug_tileX,
final int debug_tileY,
......@@ -2559,7 +2584,17 @@ public class ImageDttCPU {
final int debug_clustX = debug_tileX / tileStep;
final int debug_clustY = debug_tileY / tileStep;
///tileStep
// this.correlation2d should be non-null
boolean [] corr_calculate = null;
{
if (isCorrAll (mcorr_sel)) corr_calculate = correlation2d.selectAll();
if (isCorrDia (mcorr_sel)) corr_calculate = correlation2d.selectDiameters (corr_calculate);
if (isCorrSq (mcorr_sel)) corr_calculate = correlation2d.selectSquares (corr_calculate);
if (isCorrNeib (mcorr_sel)) corr_calculate = correlation2d.selectNeibs (corr_calculate);
if (isCorrHor (mcorr_sel)) corr_calculate = correlation2d.selectHorizontal (corr_calculate);
if (isCorrVert (mcorr_sel)) corr_calculate = correlation2d.selectVertical (corr_calculate);
correlation2d.setCorrPairs(corr_calculate); // will limit correlation pairs calculation
}
final double [][][][][][] clt_data = new double[numSensors][numcol][tilesY][tilesX][][];
final Thread[] threads = newThreadArray(threadsMax);
final AtomicInteger ai = new AtomicInteger(0);
......@@ -2580,15 +2615,6 @@ public class ImageDttCPU {
}
}
}
if (clt_mismatch != null){
for (int i = 0; i<clt_mismatch.length;i++){
clt_mismatch[i] = new double [tilesY*tilesX]; // will use only "center of mass" centers
for (int j = 0; j < clt_mismatch[i].length; j++) {
clt_mismatch[i][j] = Double.NaN;
}
}
}
// keep for now for mono, find out what do they mean for macro mode
if (isMonochrome()) {
col_weights[2] = 1.0;// green color/mono
......@@ -2656,19 +2682,6 @@ public class ImageDttCPU {
}
// add optional initialization of debug layers here
if (disparity_map != null){
for (int i = 0; i<disparity_map.length;i++){
if (i == OVEREXPOSED) {
if (saturation_imp!= null) {
disparity_map[i] = new double [tilesY*tilesX];
}
} else if (isSliceBit(i)) { // includes diffs?
disparity_map[i] = new double [tilesY*tilesX];
}
}
}
DttRad2 dtt = new DttRad2(transform_size);
dtt.set_window(window_type);
final double [] lt_window = dtt.getWin2d(); // [256]
......@@ -2696,11 +2709,12 @@ public class ImageDttCPU {
public void run() {
DttRad2 dtt = new DttRad2(transform_size);
dtt.set_window(window_type);
int tileY,tileX, clustX, clustY, cTile, tIndex; // , chn;
int tileY,tileX, clustX, clustY, cTile; // , tIndex; // , chn;
// showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays(); // just for debugging?
double centerX; // center of aberration-corrected (common model) tile, X
double centerY; //
double [][] fract_shiftsXY = new double[numSensors][];
/*
Correlation2d corr2d = new Correlation2d(
numSensors,
imgdtt_params, // ImageDttParameters imgdtt_params,
......@@ -2712,6 +2726,7 @@ public class ImageDttCPU {
imgdtt_params.getEnhOrthoWidth(isAux()), // double getEnhOrthoWidth(isAux()),
imgdtt_params.getEnhOrthoScale(isAux()), //double getEnhOrthoScale(isAux()),
(imgdtt_params.lma_debug_level > 1)); // boolean debug);
*/
double [][] rXY;
if (use_main) {
......@@ -2727,8 +2742,6 @@ public class ImageDttCPU {
double [][][] centersXY = new double [clustSize][][];
double [][][] disp_dist = new double[clustSize][numSensors][]; // used to correct 3D correlations
double [][][] corrs = new double [clustSize][][];
double [][] corr_stat = new double [clustSize][];
double [] strength = new double [clustSize];
double [][] disp_str = new double [clustSize][];
double [][] pxpy = new double [clustSize][2];
boolean debugCluster = (clustX == debug_clustX) && (clustY == debug_clustY);
......@@ -2779,29 +2792,8 @@ public class ImageDttCPU {
} else {
tile_op[mnTy][mnTx] = 0;
}
//imgdtt_params.lma_disp_range
}
if (num_good_tiles == 0) {
// fill out empty ...
for (int cTileY = 0; cTileY < tileStep; cTileY++) {
tileY = clustY * tileStep + cTileY ;
if (tileY < tilesY) {
for (int cTileX = 0; cTileX < tileStep; cTileX++) {
tileX = clustX * tileStep + cTileX ;
if (tileX < tilesX) {
cTile = cTileY * tileStep + cTileX;
tIndex = tileY * tilesX + tileX;
// int nTile = tileY * tilesX + tileX; // how is it different from tIndex?
if (clt_mismatch != null) {
for (int cam = 0; cam < numSensors; cam++) {
clt_mismatch[3*cam + 0][tIndex] = Double.NaN;
clt_mismatch[3*cam + 1][tIndex] = Double.NaN;
}
}
}
}
}
}
continue;
}
// num_good_tiles in a cluster > 0
......@@ -2812,7 +2804,7 @@ public class ImageDttCPU {
tileX = clustX * tileStep + cTileX ;
if (tileX < tilesX) {
cTile = cTileY * tileStep + cTileX;
tIndex = tileY * tilesX + tileX;
// tIndex = tileY * tilesX + tileX;
int nTile = tileY * tilesX + tileX; // how is it different from tIndex?
if (tile_op[tileY][tileX] == 0) {
disp_str[cTile] = null;
......@@ -2824,8 +2816,6 @@ public class ImageDttCPU {
centerX = tileX * transform_size + transform_size/2 - shiftX;
centerY = tileY * transform_size + transform_size/2 - shiftY;
// TODO: move port coordinates out of color channel loop
// double [][] centersXY;
// double [][] disp_dist = new double[quad][]; // used to correct 3D correlations
if ( (disparity_array == null) ||
(disparity_array[tileY] == null) ||
(Double.isNaN(disparity_array[tileY][tileX]))) {
......@@ -2933,7 +2923,6 @@ public class ImageDttCPU {
((clt_kernels == null) ? null : clt_kernels[i]), // [color][tileY][tileX][band][pixel]
clt_data[i][ncol][tileY][tileX], //double [][] clt_tile, // should be double [4][];
kernel_step,
// transform_size,
dtt,
ncol,
centersXY[cTile][i][0], // centerX, // center of aberration-corrected (common model) tile, X
......@@ -2967,7 +2956,6 @@ public class ImageDttCPU {
for (int i = 0; i < numSensors; i++) {
fract_shift( // fractional shift in transform domain. Currently uses sin/cos - change to tables with 2? rotations
clt_data[i][ncol][tileY][tileX], // double [][] clt_tile,
// transform_size,
fract_shiftsXY[i][0], // double shiftX,
fract_shiftsXY[i][1], // double shiftY,
// (globalDebugLevel > 0) && (tileX == debug_tileX) && (tileY == debug_tileY)); // external tile compare
......@@ -2991,24 +2979,11 @@ public class ImageDttCPU {
}
}// end of for (int chn = 0; chn <numcol; chn++)
// used in lwir
int tile_lma_debug_level = ((tileX == debug_tileX) && (tileY == debug_tileY))? imgdtt_params.lma_debug_level : -1;
// all color channels are done here
if (disparity_map != null){
for (int i = 0; i < disparity_map.length; i++) {
if (disparity_map[i] != null) disparity_map[i][nTile] = (
(i == DISPARITY_STRENGTH_INDEX) ||
(i == DISPARITY_INDEX_HOR_STRENGTH) ||
(i == DISPARITY_INDEX_VERT_STRENGTH)) ? 0.0 : Double.NaN; // once and for all
}
// calculate overexposed fraction
if (saturation_imp != null){
disparity_map[OVEREXPOSED][nTile] = (1.0 * overexp_all[0]) / overexp_all[1];
}
}
// calculate all selected pairs correlations
int all_pairs = imgdtt_params.dbg_pair_mask; //TODO: use tile tasks
/*
corrs[cTile] = corr2d.correlateCompositeFD( // now works with nulls for some clt_data colors
clt_data, // double [][][][][][] clt_data,
tileX, // int tileX,
......@@ -3018,68 +2993,17 @@ public class ImageDttCPU {
getScaleStrengths(), // double scale_value, // scale correlation value
col_weights, // double [] col_weights,
corr_fat_zero); // double fat_zero)
*/
corrs[cTile] = correlation2d.correlateCompositeFD(
clt_data, // double [][][][][][] clt_data,
tileX, // int tileX,
tileY, // int tileY,
correlation2d.getCorrPairs(), // boolean[] pairs_mask,
filter, // double [] lpf,
getScaleStrengths(), // double scale_value, // scale correlation value
col_weights, // double [] col_weights,
corr_fat_zero); // double fat_zero)
// calculate interpolated "strips" to match different scales and orientations (ortho/diagonal) on the
// fine (0.5 pix) grid. ortho for scale == 1 provide even/even samples (1/4 of all), diagonal ones -
// checkerboard pattern
double [][] strips = corr2d.scaleRotateInterpoateCorrelations(
corrs[cTile], // double [][] correlations,
all_pairs, // int pairs_mask,
imgdtt_params.corr_strip_hight, //); // int hwidth);
(tile_lma_debug_level > 0) ? all_pairs:0); // debugMax);
// Combine strips for selected pairs. Now using only for all available pairs.
// Other combinations are used only if requested (clt_corr_partial != null)
double [] strip_combo = corr2d.combineInterpolatedCorrelations(
strips, // double [][] strips,
all_pairs, // int pairs_mask,
imgdtt_params.corr_offset, // double offset);
imgdtt_params.twice_diagonal); // boolean twice_diagonal)
// calculate CM maximums for all mixed channels
// First get integer correlation center, relative to the center
int [] ixy = corr2d.getMaxXYInt( // find integer pair or null if below threshold
strip_combo, // double [] data,
true, // boolean axis_only,
imgdtt_params.min_corr, // double minMax, // minimal value to consider (at integer location, not interpolated)
tile_lma_debug_level > 0); // boolean debug);
// double [] corr_stat = null;
// if integer argmax was strong enough, calculate CM argmax
// will not fill out DISPARITY_INDEX_INT+1, DISPARITY_INDEX_CM+1, DISPARITY_INDEX_POLY+1
// use clt_mismatch for that
// double strength = 0.0;
// double disparity = 0.0;
if (ixy != null) {
strength[cTile] = strip_combo[ixy[0]+transform_size-1]; // strength at integer max on axis
if (disparity_map != null){
disparity_map[DISPARITY_INDEX_INT][tIndex] = -ixy[0];
disparity_map[DISPARITY_STRENGTH_INDEX][tIndex] = strength[cTile];
if (Double.isNaN(disparity_map[DISPARITY_STRENGTH_INDEX][tIndex])) {
System.out.println("BUG: 1. disparity_map[DISPARITY_STRENGTH_INDEX]["+tIndex+"] should not be NaN");
}
}
corr_stat[cTile] = corr2d.getMaxXCm( // get fractional center as a "center of mass" inside circle/square from the integer max
strip_combo, // double [] data, // [data_size * data_size]
ixy[0], // int ixcenter, // integer center x
// corr_wndy, // double [] window_y, // (half) window function in y-direction(perpendicular to disparity: for row0 ==1
// corr_wndx, // double [] window_x, // half of a window function in x (disparity) direction
(tile_lma_debug_level > 0)); // boolean debug);
}
// proceed only if CM correlation result is non-null // for compatibility with old code we need it to run regardless of the strength of the normal correlation
if (disparity_map != null){
if (corr_stat[cTile] != null) {
disparity_map[DISPARITY_INDEX_CM][tIndex] = -corr_stat[cTile][0]; // disp_str[cTile][0]; // disparity is negative X
disparity_map[DISPARITY_INDEX_INT+1][tIndex] = -corr_stat[cTile][0]/.85 + disparity_array[tileY][tileX] + disparity_corr; // disp_str[cTile][0]; // disparity is negative X
}
// hack: reuse/overwrite for target disparity
disparity_map[DISPARITY_INDEX_INT][tIndex] = disparity_array[tileY][tileX] + disparity_corr;
}
disp_str[cTile] = new double[2];
if (tile_lma_debug_level > 0) {
System.out.println("Will run getMaxXSOrtho( ) for tileX="+tileX+", tileY="+tileY);
......@@ -3087,11 +3011,13 @@ public class ImageDttCPU {
// debug new LMA correlations
int tdl = debugCluster ? tile_lma_debug_level : -3;
// find disp_str for each tile in a cluster
if (true) { // debugCluster1) {
if (debugCluster && (globalDebugLevel > -1)) { // -2)) {
System.out.println("Will run new LMA for tileX="+tileX+", tileY="+tileY);
}
double [] poly_disp = {Double.NaN, 0.0};
/*
Corr2dLMA lma2 = corr2d.corrLMA2Single(
imgdtt_params, // ImageDttParameters imgdtt_params,
false, // boolean adjust_ly, // adjust Lazy Eye
......@@ -3107,11 +3033,25 @@ public class ImageDttCPU {
tdl, // tile_lma_debug_level, //+2, // int debug_level,
tileX, // int tileX, // just for debug output
tileY); // int tileY
*/
Corr2dLMA lma2 = correlation2d.corrLMA2Single(
imgdtt_params, // ImageDttParameters imgdtt_params,
false, // false, // boolean adjust_ly, // adjust Lazy Eye
corr_wnd, // double [][] corr_wnd, // correlation window to save on re-calculation of the window
corr_wnd_inv_limited, // corr_wnd_limited, // correlation window, limited not to be smaller than threshold - used for finding max/convex areas (or null)
corrs[cTile], // corrs, // double [][] corrs,
disp_dist[cTile],
rXY, // double [][] rXY, // non-distorted X,Y offset per nominal pixel of disparity
// all that are not null in corr_tiles
correlation2d.selectAll(), // longToArray(imgdtt_params.dbg_pair_mask), // int pair_mask, // which pairs to process
null, // disp_str, //corr_stat[0], // double xcenter, // preliminary center x in pixels for largest baseline
poly_disp, // double[] poly_ds, // null or pair of disparity/strength
imgdtt_params.ortho_vasw_pwr, // double vasw_pwr, // value as weight to this power,
tdl, // tile_lma_debug_level, // +2, // int debug_level,
tileX, // int tileX, // just for debug output
tileY ); // int tileY
disp_str[cTile] = null;
if (disparity_map != null){
disparity_map[DISPARITY_INDEX_HOR][tIndex] = poly_disp[0];
disparity_map[DISPARITY_INDEX_HOR_STRENGTH][tIndex] = poly_disp[1];
}
if (lma2 != null) {
disp_str[cTile] = lma2.lmaDisparityStrength(
imgdtt_params.lmas_max_rel_rms, // maximal relative (to average max/min amplitude LMA RMS) // May be up to 0.3)
......@@ -3126,19 +3066,8 @@ public class ImageDttCPU {
double [][] ds_dbg = {disp_str[cTile]};
lma2.printStats(ds_dbg,1);
}
if (disparity_map != null){
if (disp_str[cTile] != null) {
disparity_map[DISPARITY_INDEX_POLY][tIndex] = disp_str[cTile][0];
disparity_map[DISPARITY_INDEX_POLY+1][tIndex] = disp_str[cTile][1];
}
}
}
}
//} // end of if (corr_stat != null)
// } // if (disparity_map != null){ // not null - calculate correlations
// only debug is left
}
}
}
......@@ -3148,7 +3077,7 @@ public class ImageDttCPU {
if (globalDebugLevel > 0) {
System.out.println("Will run new LMA for clustX="+clustX+", clustY="+clustY);
}
/*
Corr2dLMA lma2 = corr2d.corrLMA2Multi(
imgdtt_params, // ImageDttParameters imgdtt_params,
tileStep, // int clust_width,
......@@ -3163,6 +3092,23 @@ public class ImageDttCPU {
clust_lma_debug_level + 0, // 2, // int debug_level, // for a single cluster
clustX, // int tileX, // just for debug output
clustY ); // int tileY
*/
Corr2dLMA lma2 = correlation2d.corrLMA2Multi(
imgdtt_params, // ImageDttParameters imgdtt_params,
tileStep, // int clust_width,
corr_wnd, // double [][] corr_wnd, // correlation window to save on re-calculation of the window
corr_wnd_inv_limited, // corr_wnd_limited, // correlation window, limited not to be smaller than threshold - used for finding max/convex areas (or null)
corrs, // corrs, // double [][][] corrs,
disp_dist,
rXY, // double [][] rXY, // non-distorted X,Y offset per nominal pixel of disparity
// all that are not null in corr_tiles
correlation2d.selectAll(), // longToArray(imgdtt_params.dbg_pair_mask), // int pair_mask, // which pairs to process
disp_str, //corr_stat[0], // double xcenter, // preliminary center x in pixels for largest baseline
imgdtt_params.ortho_vasw_pwr, // double vasw_pwr, // value as weight to this power,
clust_lma_debug_level + 0, // // +2, // int debug_level,
clustX, // int tileX, // just for debug output
clustY ); // int tileY
if (lma2 != null) {
double [][] ddnd = lma2.getDdNd();
double [] stats = lma2.getStats(num_good_tiles);
......@@ -3174,7 +3120,7 @@ public class ImageDttCPU {
imgdtt_params.lma_max_area, //double lma_max_area, // maximal half-area (if > 0.0)
1.0, // imgdtt_params.lma_str_scale, // convert lma-generated strength to match previous ones - scale
0.0); // imgdtt_params.lma_str_offset); // convert lma-generated strength to match previous ones - add to result
double [][] extra_stats = lma2.getTileStats();
// double [][] extra_stats = lma2.getTileStats();
// final double [][] lazy_eye_data = new double [clustersY*clustersX][];
// calculate average disparity per cluster using a sum of the disparity_array and the result of the LMA
lazy_eye_data[nCluster] = new double [ExtrinsicAdjustment.get_INDX_LENGTH(numSensors)];
......@@ -3186,7 +3132,6 @@ public class ImageDttCPU {
tileX = clustX * tileStep + cTileX ;
if (tileX < tilesX) {
cTile = cTileY * tileStep + cTileX;
tIndex = tileY * tilesX + tileX;
if ((lma_ds[cTile] != null) && (lma_ds[cTile][1]> 0.0)) {
double w = lma_ds[cTile][1];
lazy_eye_data[nCluster][ExtrinsicAdjustment.INDX_DISP] += (lma_ds[cTile][0] + disparity_array[tileY][tileX] + disparity_corr) * w;
......@@ -3215,7 +3160,6 @@ public class ImageDttCPU {
lazy_eye_data[nCluster][ExtrinsicAdjustment.get_INDX_DYDDISP0(numSensors) + cam] /= sum_w;
lazy_eye_data[nCluster][ExtrinsicAdjustment.get_INDX_PYDIST(numSensors) + cam] /= sum_w;
}
for (int cam = 0; cam < ddnd.length; cam++) {
if (ddnd[cam] != null) { //convert to x,y from dd/nd
lazy_eye_data[nCluster][2 * cam + ExtrinsicAdjustment.INDX_X0 + 0] = ddnd[cam][0] * rXY[cam][0] - ddnd[cam][1] * rXY[cam][1];
......@@ -3232,82 +3176,6 @@ public class ImageDttCPU {
} else {
lazy_eye_data[nCluster] = null;
}
// just for debugging, can be removed
if (disparity_map != null){
double [][] lma2_ds = lma2.lmaDisparityStrength(
imgdtt_params.lma_max_rel_rms, // maximal relative (to average max/min amplitude LMA RMS) // May be up to 0.3)
imgdtt_params.lma_min_strength, // minimal composite strength (sqrt(average amp squared over absolute RMS)
imgdtt_params.lma_min_ac, // minimal of A and C coefficients maximum (measures sharpest point/line)
imgdtt_params.lma_min_min_ac, // minimal of A and C coefficients minimum (measures sharpest point)
imgdtt_params.lma_max_area, //double lma_max_area, // maximal half-area (if > 0.0)
imgdtt_params.lma_str_scale, // convert lma-generated strength to match previous ones - scale
imgdtt_params.lma_str_offset); // convert lma-generated strength to match previous ones - add to result
for (int cTileY = 0; cTileY < tileStep; cTileY++) {
tileY = clustY * tileStep + cTileY ;
if (tileY < tilesY) {
for (int cTileX = 0; cTileX < tileStep; cTileX++) {
tileX = clustX * tileStep + cTileX ;
if (tileX < tilesX) {
cTile = cTileY * tileStep + cTileX;
tIndex = tileY * tilesX + tileX;
// int nTile = tileY * tilesX + tileX; // how is it different from tIndex?
for (int cam = 0; cam < ddnd.length; cam++) {
if ((clt_mismatch != null) && (ddnd[cam] != null)) {
if (imgdtt_params.lma_diff_xy) {
clt_mismatch[3*cam + 0][tIndex] =
ddnd[cam][0] * rXY[cam][0] - ddnd[cam][1] * rXY[cam][1];
clt_mismatch[3*cam + 1][tIndex] =
ddnd[cam][0] * rXY[cam][1] + ddnd[cam][1] * rXY[cam][0];
} else {
clt_mismatch[3*cam + 0][tIndex] = ddnd[cam][0];
clt_mismatch[3*cam + 1][tIndex] = ddnd[cam][1];
}
}
if (stats != null) {
disparity_map[IMG_DIFF0_INDEX+0][tIndex] = stats[0];
disparity_map[IMG_DIFF0_INDEX+1][tIndex] = stats[1];
disparity_map[IMG_DIFF0_INDEX+2][tIndex] = stats[2];
// disparity_map[IMG_DIFF0_INDEX+3][tIndex] = stats[3];
}
if ((lma2_ds != null) && ((lma2_ds[cTile] != null))) {
// composite new disparity
disparity_map[DISPARITY_INDEX_VERT][tIndex] = lma2_ds[cTile][0]+ disparity_array[tileY][tileX] + disparity_corr;
disparity_map[DISPARITY_INDEX_VERT_STRENGTH][tIndex] = lma2_ds[cTile][1];
if (clt_mismatch != null) {
clt_mismatch[3*0 + 2][tIndex] =
(lma2_ds[cTile][1] - imgdtt_params.lma_str_offset)/imgdtt_params.lma_str_scale - imgdtt_params.lma_min_strength;
}
}
}
if (extra_stats != null) {
if (extra_stats[cTile] != null) {
disparity_map[DISPARITY_INDEX_CM+1][tIndex] = extra_stats[cTile][0];
disparity_map[DISPARITY_VARIATIONS_INDEX][tIndex] = extra_stats[cTile][2];
disparity_map[OVEREXPOSED][tIndex] = extra_stats[cTile][3];
if (clt_mismatch != null) {
clt_mismatch[3*1 + 2][tIndex] = extra_stats[cTile][0];
clt_mismatch[3*2 + 2][tIndex] = extra_stats[cTile][2];
clt_mismatch[3*3 + 2][tIndex] = extra_stats[cTile][3];
}
} else {
disparity_map[DISPARITY_INDEX_CM+1][tIndex] = Double.NaN;
disparity_map[DISPARITY_VARIATIONS_INDEX][tIndex] = Double.NaN;
disparity_map[OVEREXPOSED][tIndex] = Double.NaN;
if (clt_mismatch != null) {
clt_mismatch[3*1 + 2][tIndex] = Double.NaN;
clt_mismatch[3*2 + 2][tIndex] = Double.NaN;
clt_mismatch[3*3 + 2][tIndex] = Double.NaN;
}
}
}
}
}
}
}
}
/**/
}
}
}
......@@ -3316,16 +3184,9 @@ public class ImageDttCPU {
}
startAndJoin(threads);
// final double [][] dbg_distort = debug_distort? (new double [4*quad][tilesX*tilesY]) : null;
if ((dbg_distort != null) &&(globalDebugLevel >=0)) {
(new ShowDoubleFloatArrays()).showArrays(dbg_distort, tilesX, tilesY, true, "disparity_distortions"); // , dbg_titles);
}
/*
if (dbg_ports_coords != null) {
(new showDoubleFloatArrays()).showArrays(dbg_ports_coords, tilesX, tilesY, true, "ports_coordinates", dbg_titles);
}
*/
return lazy_eye_data; // clt_data;
}
......@@ -3380,6 +3241,7 @@ public class ImageDttCPU {
final double shiftX, // shift image horizontally (positive - right) - just for testing
final double shiftY, // shift image vertically (positive - down)
final int mcorr_sel, // Which pairs to correlate // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
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)
......@@ -3402,13 +3264,12 @@ public class ImageDttCPU {
if (correlation2d != null){
// Initialize correlation pairs selection to be used by all threads
boolean [] corr_calculate = null;
if (imgdtt_params.getMcorrAll (numSensors)) corr_calculate = correlation2d.selectAll();
if (imgdtt_params.getMcorrDia (numSensors)) corr_calculate = correlation2d.selectDiameters (corr_calculate);
if (imgdtt_params.getMcorrSq (numSensors)) corr_calculate = correlation2d.selectSquares (corr_calculate);
if (imgdtt_params.getMcorrNeib(numSensors)) corr_calculate = correlation2d.selectNeibs (corr_calculate);
if (imgdtt_params.getMcorrHor (numSensors)) corr_calculate = correlation2d.selectHorizontal (corr_calculate);
if (imgdtt_params.getMcorrVert(numSensors)) corr_calculate = correlation2d.selectVertical (corr_calculate);
if (isCorrAll (mcorr_sel)) corr_calculate = correlation2d.selectAll();
if (isCorrDia (mcorr_sel)) corr_calculate = correlation2d.selectDiameters (corr_calculate);
if (isCorrSq (mcorr_sel)) corr_calculate = correlation2d.selectSquares (corr_calculate);
if (isCorrNeib (mcorr_sel)) corr_calculate = correlation2d.selectNeibs (corr_calculate);
if (isCorrHor (mcorr_sel)) corr_calculate = correlation2d.selectHorizontal (corr_calculate);
if (isCorrVert (mcorr_sel)) corr_calculate = correlation2d.selectVertical (corr_calculate);
correlation2d.setCorrPairs(corr_calculate); // will limit correlation pairs calculation
correlation2d.generateResample( // should be called before
mcorr_comb_width, // combined correlation tile width
......@@ -3466,8 +3327,8 @@ public class ImageDttCPU {
debug_offsets[i][j] = imgdtt_params.lma_dbg_offset[i][j]*imgdtt_params.lma_dbg_scale;
}
final double [] dbg_corr_shift =((imgdtt_params.pcorr_dbg_offsx != 0.0) || (imgdtt_params.pcorr_dbg_offsy != 0.0))?
(new double [] {imgdtt_params.pcorr_dbg_offsx,imgdtt_params.pcorr_dbg_offsy}):null;
// final double [] dbg_corr_shift =((imgdtt_params.pcorr_dbg_offsx != 0.0) || (imgdtt_params.pcorr_dbg_offsy != 0.0))?
// (new double [] {imgdtt_params.pcorr_dbg_offsx,imgdtt_params.pcorr_dbg_offsy}):null;
final boolean macro_mode = macro_scale != 1; // correlate tile data instead of the pixel data
final int numcol = 3; // number of colors // keep the same, just do not use [0] and [1], [2] - green
final int nTilesInChn=tilesX*tilesY;
......@@ -3571,13 +3432,13 @@ public class ImageDttCPU {
System.out.println("clt_aberrations_quad_corr(): width="+width+" height="+height+" transform_size="+transform_size+
" debug_tileX="+debug_tileX+" debug_tileY="+debug_tileY+" globalDebugLevel="+globalDebugLevel);
}
final int transform_len = transform_size * transform_size;
// final int transform_len = transform_size * transform_size;
final double [] filter = doubleGetCltLpfFd(corr_sigma);
final double [] filter_rb = doubleGetCltLpfFd(imgdtt_params.pcorr_sigma_rb);
final double [] filter_common = doubleGetCltLpfFd(imgdtt_params.getCorrSigma(isMonochrome()));
final double pcorr_fat_zero = imgdtt_params.getFatZero(isMonochrome());
// final double [] filter_rb = doubleGetCltLpfFd(imgdtt_params.pcorr_sigma_rb);
// final double [] filter_common = doubleGetCltLpfFd(imgdtt_params.getCorrSigma(isMonochrome()));
// final double pcorr_fat_zero = imgdtt_params.getFatZero(isMonochrome());
// prepare disparity maps and weights
final int max_search_radius = (int) Math.abs(max_corr_radius); // use negative max_corr_radius for squares instead of circles?
......@@ -3657,9 +3518,6 @@ public class ImageDttCPU {
double centerX; // center of aberration-corrected (common model) tile, X
double centerY; //
double [][] fract_shiftsXY = new double[numSensors][];
/// double [][] tcorr_combo = null; // [15*15] pixel space
/// double [][][] tcorr_partial = null; // [quad][numcol+1][15*15]
/// double [][][][] tcorr_tpartial = null; // [quad][numcol+1][4][8*8]
double [] ports_rgb = null;
double [][] rXY;
......@@ -3668,15 +3526,7 @@ public class ImageDttCPU {
} else {
rXY = geometryCorrection.getRXY(false); // boolean use_rig_offsets,
}
/*
correlation2d.createOrtoNotch( // TODO: maybe it will not be used anumore
imgdtt_params.getEnhOrthoWidth(isAux()), // double getEnhOrthoWidth(isAux()),
imgdtt_params.getEnhOrthoScale(isAux()), //double getEnhOrthoScale(isAux()),
(imgdtt_params.lma_debug_level > 1)); // boolean debug);
*/
for (int nTile = ai.getAndIncrement(); nTile < nTilesInChn; nTile = ai.getAndIncrement()) {
tileY = nTile /tilesX;
tileX = nTile % tilesX;
tIndex = tileY * tilesX + tileX;
......@@ -3689,14 +3539,6 @@ public class ImageDttCPU {
}
}
}
int corr_mask = getPairMask(tile_op[tileY][tileX]); // which pairs to combine in the combo: 1 - top, 2 bottom, 4 - left, 8 - right
// mask out pairs that use missing channels
for (int i = 0; i< CORR_PAIRS.length; i++){
if ((((1 << CORR_PAIRS[i][0]) & img_mask) == 0) || (((1 << CORR_PAIRS[i][1]) & img_mask) == 0)) {
corr_mask &= ~ (1 << i);
}
}
boolean debugTile =(tileX == debug_tileX) && (tileY == debug_tileY) && (globalDebugLevel > -1);
boolean debugTile0 =(tileX == debug_tileX) && (tileY == debug_tileY) && (globalDebugLevel > -3);
final int [] overexp_all = (saturation_imp != null) ? ( new int [2]): null;
......@@ -4019,8 +3861,6 @@ public class ImageDttCPU {
disparity_map[OVEREXPOSED][nTile] = (1.0 * overexp_all[0]) / overexp_all[1];
}
// calculate all selected pairs correlations
int all_pairs = imgdtt_params.dbg_pair_mask; //TODO: use tile tasks
double [][] corr_tiles = correlation2d.correlateCompositeFD(
clt_data, // double [][][][][][] clt_data,
tileX, // int tileX,
......@@ -4147,33 +3987,6 @@ public class ImageDttCPU {
disparity_map[DISPARITY_INDEX_VERT_STRENGTH][tIndex] = vert_pair1[1];
}
}
} else {
// for compatibility with old code executed unconditionally. TODO: Move to if (corr_stat != null) ... condition below
/*
double [] hor_pair1 = corr2d.getMaxXSOrtho(
corrs, // double [][] correlations,
Correlation2d.getMaskHorizontal(1), // int pairs_mask,
imgdtt_params.corr_offset, // double corr_offset,
true, // boolean symmetric, // for comparing with old implementation average with symmetrical before multiplication
false, // boolean is_vert, // transpose X/Y
tile_lma_debug_level > 0); // boolean debug);
if (hor_pair1 != null) {
disparity_map[DISPARITY_INDEX_HOR][tIndex] = -hor_pair1[0];
disparity_map[DISPARITY_INDEX_HOR_STRENGTH][tIndex] = hor_pair1[1];
}
double [] vert_pair1 = corr2d.getMaxXSOrtho(
corrs, // double [][] correlations,
Correlation2d.getMaskVertical(1), // int pairs_mask,
imgdtt_params.corr_offset, // double corr_offset,
true, // boolean symmetric, // for comparing with old implementation average with symmetrical before multiplication
true, // boolean is_vert, // transpose X/Y
tile_lma_debug_level > 0); // boolean debug);
if (vert_pair1 != null) {
disparity_map[DISPARITY_INDEX_VERT][tIndex] = -vert_pair1[0];
disparity_map[DISPARITY_INDEX_VERT_STRENGTH][tIndex] = vert_pair1[1];
}
*/
}
// proceed only if CM correlation result is non-null // for compatibility with old code we need it to run regardless of the strength of the normal correlation
if (corr_stat != null) {
......@@ -4231,8 +4044,6 @@ public class ImageDttCPU {
} // end of if (corr_stat != null)
} // if (disparity_map != null){ // not null - calculate correlations
// only debug is left
if (texture_tiles !=null) {
if ((extra_disparity != 0) && !getForcedDisparity(tile_op[tileY][tileX])){ // 0 - adjust disparity, 1 - use provided
......@@ -4242,7 +4053,6 @@ public class ImageDttCPU {
if (clt_data[i][ncol] != null) {
fract_shift( // fractional shift in transform domain. Currently uses sin/cos - change to tables with 2? rotations
clt_data[i][ncol][tileY][tileX], // double [][] clt_tile,
// transform_size,
extra_disparity * port_offsets[i][0] / corr_magic_scale, // double shiftX,
extra_disparity * port_offsets[i][1] / corr_magic_scale, // double shiftY,
// (globalDebugLevel > 0) && (tileX == debug_tileX) && (tileY == debug_tileY)); // external tile compare
......@@ -4404,16 +4214,10 @@ public class ImageDttCPU {
}
startAndJoin(threads);
// final double [][] dbg_distort = debug_distort? (new double [4*quad][tilesX*tilesY]) : null;
if ((dbg_distort != null) &&(globalDebugLevel >=0)) {
(new ShowDoubleFloatArrays()).showArrays(dbg_distort, tilesX, tilesY, true, "disparity_distortions"); // , dbg_titles);
}
/*
if (dbg_ports_coords != null) {
(new showDoubleFloatArrays()).showArrays(dbg_ports_coords, tilesX, tilesY, true, "ports_coordinates", dbg_titles);
}
*/
return clt_data;
}
......
......@@ -101,6 +101,9 @@ public class ImageDttParameters {
public boolean mcorr_hor_multi = true; // all horizontal
public boolean mcorr_vert = true; // all vertical (2 pairs for quad, 8 - for lwir16)
public boolean mcorr_vert_multi = true; // all vertical
//final int corr_sel, // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
public int mcorr_sel_ly = 1; // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
public int mcorr_sel_ly_multi = 2+4+8; // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
public boolean mcorr_cons_all = true; // consolidate all available pairs
......@@ -270,6 +273,10 @@ public class ImageDttParameters {
return (numSens > mcorr_multi) ? mcorr_vert_multi : mcorr_vert;
}
public int getMcorrSelLY(int numSens) {
return (numSens > mcorr_multi) ? mcorr_sel_ly_multi : mcorr_sel_ly;
}
public void dialogQuestions(GenericJTabbedDialog gd) {
gd.addCheckbox ("Debug CPU->GPU matching", this.gpu_mode_debug,
......@@ -410,8 +417,10 @@ public class ImageDttParameters {
"All vertical pairs. N: 2 for quad, 8 for lwir16");
gd.addCheckbox ("Calculate vertical pairs for multi cameras", this.mcorr_vert_multi,
"All vertical pairs. N: 2 for quad, 8 for lwir16");
gd.addNumericField ("Select correlation pairs for LY for small cameras", this.mcorr_sel_ly, 0, 3, "",
" +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert");
gd.addNumericField ("Select correlation pairs for LY for multi cameras", this.mcorr_sel_ly_multi, 0, 3, "",
" +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert");
gd.addCheckbox ("Combine all pairs", this.mcorr_cons_all,
"Combine all calculated correlation pairs");
......@@ -718,6 +727,9 @@ public class ImageDttParameters {
this.mcorr_vert = gd.getNextBoolean();
this.mcorr_vert_multi = gd.getNextBoolean();
this.mcorr_sel_ly= (int) gd.getNextNumber();
this.mcorr_sel_ly_multi=(int)gd.getNextNumber();
this.mcorr_cons_all = gd.getNextBoolean();
this.mcorr_cons_dia = gd.getNextBoolean();
this.mcorr_cons_sq = gd.getNextBoolean();
......@@ -902,6 +914,9 @@ public class ImageDttParameters {
properties.setProperty(prefix+"mcorr_vert", this.mcorr_vert +"");
properties.setProperty(prefix+"mcorr_vert_multi", this.mcorr_vert_multi +"");
properties.setProperty(prefix+"mcorr_sel_ly", this.mcorr_sel_ly +"");
properties.setProperty(prefix+"mcorr_sel_ly_multi", this.mcorr_sel_ly_multi +"");
properties.setProperty(prefix+"mcorr_cons_all", this.mcorr_cons_all +"");
properties.setProperty(prefix+"mcorr_cons_dia", this.mcorr_cons_dia +"");
properties.setProperty(prefix+"mcorr_cons_sq", this.mcorr_cons_sq +"");
......@@ -1088,6 +1103,8 @@ public class ImageDttParameters {
if (properties.getProperty(prefix+"mcorr_hor_multi")!=null) this.mcorr_hor_multi=Boolean.parseBoolean(properties.getProperty(prefix+"mcorr_hor_multi"));
if (properties.getProperty(prefix+"mcorr_vert")!=null) this.mcorr_vert=Boolean.parseBoolean(properties.getProperty(prefix+"mcorr_vert"));
if (properties.getProperty(prefix+"mcorr_vert_multi")!=null) this.mcorr_vert_multi=Boolean.parseBoolean(properties.getProperty(prefix+"mcorr_vert_multi"));
if (properties.getProperty(prefix+"mcorr_sel_ly")!=null) this.mcorr_sel_ly=Integer.parseInt(properties.getProperty(prefix+"mcorr_sel_ly"));
if (properties.getProperty(prefix+"mcorr_sel_ly_multi")!=null) this.mcorr_sel_ly_multi=Integer.parseInt(properties.getProperty(prefix+"mcorr_sel_ly_multi"));
if (properties.getProperty(prefix+"mcorr_cons_all")!=null) this.mcorr_cons_all=Boolean.parseBoolean(properties.getProperty(prefix+"mcorr_cons_all"));
if (properties.getProperty(prefix+"mcorr_cons_dia")!=null) this.mcorr_cons_dia=Boolean.parseBoolean(properties.getProperty(prefix+"mcorr_cons_dia"));
......@@ -1273,6 +1290,9 @@ public class ImageDttParameters {
idp.mcorr_vert= this.mcorr_vert;
idp.mcorr_vert_multi= this.mcorr_vert_multi;
idp.mcorr_sel_ly= this.mcorr_sel_ly;
idp.mcorr_sel_ly_multi= this.mcorr_sel_ly_multi;
idp.mcorr_cons_all= this.mcorr_cons_all;
idp.mcorr_cons_dia= this.mcorr_cons_dia;
idp.mcorr_cons_sq= this.mcorr_cons_sq;
......
......@@ -4967,6 +4967,7 @@ public class QuadCLT extends QuadCLTCPU {
// use new, LMA-based mismatch calculation
double [][] lazy_eye_data = null;
if ((gpuQuad == null) || !(isAux()?clt_parameters.gpu_use_aux_adjust : clt_parameters.gpu_use_main_adjust)) { // CPU
/*
lazy_eye_data = image_dtt.cltMeasureLazyEye ( // returns d,s lazy eye parameters
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
tile_op, // per-tile operation bit codes
......@@ -4997,6 +4998,35 @@ public class QuadCLT extends QuadCLTCPU {
clt_parameters.tileY, // final int debug_tileY,
threadsMax,
debugLevel - 2);
*/
lazy_eye_data = image_dtt.cltMeasureLazyEye ( // returns d,s lazy eye parameters
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
tile_op, // final int [][] tile_op, // [tilesY][tilesX] - what to do - 0 - nothing for this tile
disparity_array, // final double [][] disparity_array, // [tilesY][tilesX] - individual per-tile expected disparity
image_data, // final double [][][] imade_data, // first index - number of image in a quad
saturation_imp, // final boolean [][] saturation_imp, // (near) saturated pixels or null
tilesX * image_dtt.transform_size, // final int width,
clt_parameters.getFatZero(isMonochrome()), // final double corr_fat_zero, // add to denominator to modify phase correlation (same units as data1, data2). <0 - pure sum
clt_parameters.corr_red, // final double corr_red,
clt_parameters.corr_blue, // final double corr_blue,
clt_parameters.getCorrSigma(image_dtt.isMonochrome()), // final double corr_sigma,
min_corr_selected, // 0.0001; //final double min_corr, // 0.02; // minimal correlation value to consider valid
geometryCorrection, // final GeometryCorrection geometryCorrection,
null, // final GeometryCorrection geometryCorrection_main, // if not null correct this camera (aux) to the coordinates of the main
clt_kernels, // final double [][][][][][] clt_kernels, // [channel_in_quad][color][tileY][tileX][band][pixel] , size should match image (have 1 tile around)
clt_parameters.kernel_step, // final int kernel_step,
clt_parameters.clt_window, // final int window_type,
shiftXY, // final double [][] shiftXY, // [port]{shiftX,shiftY}
disparity_corr, // final double disparity_corr, // disparity at infinity
clt_parameters.shift_x, // final double shiftX, // shift image horizontally (positive - right) - just for testing
clt_parameters.shift_y, // final double shiftY, // shift image vertically (positive - down)
clt_parameters.tileStep, // final int tileStep, // process tileStep x tileStep cluster of tiles when adjusting lazy eye parameters
clt_parameters.img_dtt.getMcorrSelLY(getNumSensors()), // final int mcorr_sel, // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
clt_parameters.tileX, // final int debug_tileX,
clt_parameters.tileY, // final int debug_tileY,
threadsMax, // final int threadsMax, // maximal number of threads to launch
debugLevel - 2); // final int globalDebugLevel)
} else {// GPU
// First - measure and get fcorr_td, fdisp_dist, fpxpy
float [][][][] fcorr_td = new float[tilesY][tilesX][][];
......
......@@ -4715,8 +4715,16 @@ public class QuadCLTCPU {
for (int i = 0; i < fine_corr0.length; i++) {
this.fine_corr[i] = fine_corr0[i];
}
}
//getNumSensors()
int mcorr_sel = ImageDtt. corrSelEncode(
clt_parameters.img_dtt.getMcorrAll (getNumSensors()), // boolean sel_all,
clt_parameters.img_dtt.getMcorrDia (getNumSensors()), // boolean sel_dia,
clt_parameters.img_dtt.getMcorrSq (getNumSensors()), // boolean sel_sq,
clt_parameters.img_dtt.getMcorrNeib (getNumSensors()), // boolean sel_neib,
clt_parameters.img_dtt.getMcorrHor (getNumSensors()), // boolean sel_hor,
clt_parameters.img_dtt.getMcorrVert (getNumSensors())); // boolean sel_vert);
if (debugLevel > 1000) texture_tiles = null; // FIXME: until texture generation for multi-cam is fixed
double [][][][][][] clt_data = image_dtt.clt_aberrations_quad_corr(
......@@ -4764,7 +4772,7 @@ public class QuadCLTCPU {
clt_parameters.corr_magic_scale, // still not understood coefficient that reduces reported disparity value. Seems to be around 0.85
clt_parameters.shift_x, // final int shiftX, // shift image horizontally (positive - right) - just for testing
clt_parameters.shift_y, // final int shiftY, // shift image vertically (positive - down)
mcorr_sel, // final int mcorr_sel, // Which pairs to correlate // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
clt_parameters.img_dtt.mcorr_comb_width, // final int mcorr_comb_width, // combined correlation tile width
clt_parameters.img_dtt.mcorr_comb_height, // final int mcorr_comb_height, // combined correlation tile full height
clt_parameters.img_dtt.mcorr_comb_offset, // final int mcorr_comb_offset, // combined correlation tile height offset: 0 - centered (-height/2 to height/2), height/2 - only positive (0 to height)
......@@ -6215,6 +6223,7 @@ public class QuadCLTCPU {
z_correction +=clt_parameters.z_corr_map.get(name);// not used in lwir
}
final double disparity_corr = (z_correction == 0) ? 0.0 : geometryCorrection.getDisparityFromZ(1.0/z_correction);
/*
double [][] lazy_eye_data = image_dtt.cltMeasureLazyEye(
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
tile_op, // per-tile operation bit codes
......@@ -6243,6 +6252,36 @@ public class QuadCLTCPU {
clt_parameters.tileY, // final int debug_tileY, -1234 will cause port coordinates debug images
threadsMax,
debugLevel);
*/
double [][] lazy_eye_data = image_dtt.cltMeasureLazyEye ( // returns d,s lazy eye parameters
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
tile_op, // final int [][] tile_op, // [tilesY][tilesX] - what to do - 0 - nothing for this tile
disparity_array, // final double [][] disparity_array, // [tilesY][tilesX] - individual per-tile expected disparity
image_data, // final double [][][] imade_data, // first index - number of image in a quad
saturation_imp, // final boolean [][] saturation_imp, // (near) saturated pixels or null
tilesX * image_dtt.transform_size, // final int width,
clt_parameters.getFatZero(isMonochrome()), // final double corr_fat_zero, // add to denominator to modify phase correlation (same units as data1, data2). <0 - pure sum
clt_parameters.corr_red, // final double corr_red,
clt_parameters.corr_blue, // final double corr_blue,
clt_parameters.getCorrSigma(image_dtt.isMonochrome()), // final double corr_sigma,
min_corr_selected, // 0.0001; //final double min_corr, // 0.02; // minimal correlation value to consider valid
geometryCorrection, // final GeometryCorrection geometryCorrection,
null, // final GeometryCorrection geometryCorrection_main, // if not null correct this camera (aux) to the coordinates of the main
clt_kernels, // final double [][][][][][] clt_kernels, // [channel_in_quad][color][tileY][tileX][band][pixel] , size should match image (have 1 tile around)
clt_parameters.kernel_step, // final int kernel_step,
clt_parameters.clt_window, // final int window_type,
shiftXY, // final double [][] shiftXY, // [port]{shiftX,shiftY}
disparity_corr, // final double disparity_corr, // disparity at infinity
clt_parameters.shift_x, // final double shiftX, // shift image horizontally (positive - right) - just for testing
clt_parameters.shift_y, // final double shiftY, // shift image vertically (positive - down)
clt_parameters.tileStep, // final int tileStep, // process tileStep x tileStep cluster of tiles when adjusting lazy eye parameters
clt_parameters.img_dtt.getMcorrSelLY(getNumSensors()), // final int mcorr_sel, // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
clt_parameters.tileX, // final int debug_tileX,
clt_parameters.tileY, // final int debug_tileY,
threadsMax, // final int threadsMax, // maximal number of threads to launch
debugLevel - 2); // final int globalDebugLevel)
if (lazy_eye_data != null) {
int clustersX= (tilesX + clt_parameters.tileStep - 1) / clt_parameters.tileStep;
......@@ -12233,7 +12272,9 @@ public class QuadCLTCPU {
"LY-combo_scan-"+scan+"_post"); //String title)
}
// use new, LMA-based mismatch calculation
double [][] lazy_eye_data = image_dtt.cltMeasureLazyEye ( // returns d,s lazy eye parameters
double [][] lazy_eye_data;
/*
lazy_eye_data = image_dtt.cltMeasureLazyEye ( // returns d,s lazy eye parameters
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
tile_op, // per-tile operation bit codes
disparity_array, // clt_parameters.disparity, // final double disparity,
......@@ -12252,7 +12293,6 @@ public class QuadCLTCPU {
null, // final GeometryCorrection geometryCorrection_main, // if not null correct this camera (aux) to the coordinates of the main
clt_kernels, // final double [][][][][][] clt_kernels, // [channel_in_quad][color][tileY][tileX][band][pixel] , size should match image (have 1 tile around)
clt_parameters.kernel_step,
// image_dtt.transform_size,
clt_parameters.clt_window,
shiftXY, //
disparity_corr, // final double disparity_corr, // disparity at infinity
......@@ -12263,6 +12303,34 @@ public class QuadCLTCPU {
clt_parameters.tileY, // final int debug_tileY,
threadsMax,
debugLevel - 2); // -0);
*/
lazy_eye_data = image_dtt.cltMeasureLazyEye ( // returns d,s lazy eye parameters
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
tile_op, // final int [][] tile_op, // [tilesY][tilesX] - what to do - 0 - nothing for this tile
disparity_array, // final double [][] disparity_array, // [tilesY][tilesX] - individual per-tile expected disparity
image_data, // final double [][][] imade_data, // first index - number of image in a quad
saturation_imp, // final boolean [][] saturation_imp, // (near) saturated pixels or null
tilesX * image_dtt.transform_size, // final int width,
clt_parameters.getFatZero(isMonochrome()), // final double corr_fat_zero, // add to denominator to modify phase correlation (same units as data1, data2). <0 - pure sum
clt_parameters.corr_red, // final double corr_red,
clt_parameters.corr_blue, // final double corr_blue,
clt_parameters.getCorrSigma(image_dtt.isMonochrome()), // final double corr_sigma,
min_corr_selected, // 0.0001; //final double min_corr, // 0.02; // minimal correlation value to consider valid
geometryCorrection, // final GeometryCorrection geometryCorrection,
null, // final GeometryCorrection geometryCorrection_main, // if not null correct this camera (aux) to the coordinates of the main
clt_kernels, // final double [][][][][][] clt_kernels, // [channel_in_quad][color][tileY][tileX][band][pixel] , size should match image (have 1 tile around)
clt_parameters.kernel_step, // final int kernel_step,
clt_parameters.clt_window, // final int window_type,
shiftXY, // final double [][] shiftXY, // [port]{shiftX,shiftY}
disparity_corr, // final double disparity_corr, // disparity at infinity
clt_parameters.shift_x, // final double shiftX, // shift image horizontally (positive - right) - just for testing
clt_parameters.shift_y, // final double shiftY, // shift image vertically (positive - down)
clt_parameters.tileStep, // final int tileStep, // process tileStep x tileStep cluster of tiles when adjusting lazy eye parameters
clt_parameters.img_dtt.getMcorrSelLY(getNumSensors()), // final int mcorr_sel, // +1 - all, +2 - dia, +4 - sq, +8 - neibs, +16 - hor + 32 - vert
clt_parameters.tileX, // final int debug_tileX,
clt_parameters.tileY, // final int debug_tileY,
threadsMax, // final int threadsMax, // maximal number of threads to launch
debugLevel - 2); // final int globalDebugLevel)
scan.setLazyEyeData(lazy_eye_data);
scan.is_measured = true; // but no disparity map/textures
scan.is_combo = false;
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment