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imagej-elphel
Commit 6c2fb8a0 authored by Andrey Filippov's avatar Andrey Filippov
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refactoring, alignment with LWIR sensors

parent 04a6a7dd
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src/main/java/com/elphel/imagej/cameras/EyesisCorrectionParameters.java
View file @ 6c2fb8a0
......@@ -1247,7 +1247,9 @@ public class EyesisCorrectionParameters {
String [] extensions = getSourceSuffixes();// ={this.sourceSuffix};
String [] prefixes = getSourcePrefixes();
int num_chn_files = numSubCameras + ((aux_camera != null)?aux_camera.numSubCameras : 0);
int num_chn_main = numSubCameras;
int num_chn_aux = ((aux_camera != null)?aux_camera.numSubCameras : 0);
int num_chn_files = num_chn_main + num_chn_aux;
extensions[0] = sourceSuffix;
prefixes[0] = sourcePrefix;
MultipleExtensionsFileFilter setFilter = new MultipleExtensionsFileFilter(prefixes,extensions,"Image sets");
......@@ -1281,7 +1283,10 @@ public class EyesisCorrectionParameters {
// String [] setChnFiles = files[nFile].list(setFilter);
File [] setChnFiles = files[nFile].listFiles(setFilter);
int num_match = setChnFiles.length;
if (num_match == num_chn_files) { // only use sets of exact number of files
if ( (num_match == num_chn_files) || // all files for main and aux
(num_match == num_chn_main) || // only main camera files
(num_match == num_chn_aux)) // only aux camera files
{ // only use sets of exact number of files
setDirList.add(files[nFile]);
for (File f: setChnFiles) {
setFilesList.add(f);
......
src/main/java/com/elphel/imagej/correction/EyesisDCT.java
View file @ 6c2fb8a0
......@@ -1220,7 +1220,7 @@ public class EyesisDCT {
}
if (this.correctionsParameters.deconvolve) { // process with DCT, otherwise use simple debayer
ImageDtt image_dtt = new ImageDtt(false); // Bayer, not monochrome
ImageDtt image_dtt = new ImageDtt(false, 1.0); // Bayer( not monochrome), scale correlation strengths
double [][][][] dct_data = image_dtt.mdctStack(
stack,
channel,
......
src/main/java/com/elphel/imagej/tileprocessor/AlignmentCorrection.java
View file @ 6c2fb8a0
......@@ -1775,7 +1775,8 @@ B = |+dy0 -dy1 -2*dy3 |
final int hist_min_samples,
final boolean hist_norm_center, // if there are more tiles that fit than min_samples, replace with
final double inf_fraction, // fraction of the weight for the infinity tiles
CLTParameters clt_parameters,
final boolean right_left, // equalize weights of right/left FoV (use with horizon in both halves and gross infinity correction)
CLTParameters clt_parameters,
double [][] scans_14,
double [][] target_disparity, // null or programmed disparity (1 per each 14 entries of scans_14)
int tilesX,
......@@ -1878,7 +1879,8 @@ B = |+dy0 -dy1 -2*dy3 |
}
if (debugLevel > -2) {
System.out.println("lazyEyeCorrection() 1: removing tiles with residual disparity absoulte value > "+lazyEyeCompDiff);
System.out.println("lazyEyeCorrection().a 1: removing tiles with residual disparity absolute value > "+lazyEyeCompDiff);
// System.out.println("lazyEyeCorrection().a 1: removing tiles with residual disparity absolute value > "+(2*lazyEyeCompDiff));
}
double [][] combo_mismatch = new double [NUM_SLICES][num_tiles];
......@@ -1891,6 +1893,7 @@ B = |+dy0 -dy1 -2*dy3 |
double w = filtered_scans[ns * NUM_SLICES + 1][nTile];
if (w > 0.0){
double disp = filtered_scans[ns * NUM_SLICES + 0][nTile];
// if (Math.abs(disp) <= 2.0*lazyEyeCompDiff) {
if (Math.abs(disp) <= lazyEyeCompDiff) {
for (int i = 2; i < NUM_SLICES; i++) if (i != 1){
combo_mismatch[i][nTile] += filtered_scans[ns * NUM_SLICES + i][nTile] * w;
......@@ -2214,6 +2217,29 @@ B = |+dy0 -dy1 -2*dy3 |
System.out.println("lazyEyeCorrection(): number of all samples="+inf_samples_list.size()+", total weight = "+inf_weight);
}
if (right_left) {
System.out.println("Balancing right/left part of FoV weights, width = "+tilesX+" tiles");
double [] right_left_weights = {0.0, 0.0};
for (Sample s: inf_samples_list) {
int rl = (s.tile % tilesX) / (tilesX/2);
right_left_weights[rl] += s.weight;
}
System.out.println("Weights: left:"+ right_left_weights[0]+", right:"+ right_left_weights[1]);
for (Sample s: inf_samples_list) {
int rl = (s.tile % tilesX) / (tilesX/2);
s.weight *= right_left_weights[1 - rl];
}
// just verifying
right_left_weights[0] = 0.0;
right_left_weights[1] = 0.0;
for (Sample s: inf_samples_list) {
int rl = (s.tile % tilesX) / (tilesX/2);
right_left_weights[rl] += s.weight;
}
System.out.println("Weights after balancing: left:"+ right_left_weights[0]+", right:"+ right_left_weights[1]);
}
if (debugLevel > 0) {
String [] prefixes = {"disparity", "strength", "dx0", "dy0", "dx1", "dy1", "dx2", "dy2", "dx3", "dy3"};
......@@ -3369,6 +3395,11 @@ B = |+dy0 -dy1 -2*dy3 |
int dbg_height = qc.tp.getTilesY()*qc.tp.getTileSize();
int dbg_owidth = dbg_width/dbg_decimate;
int dbg_oheight = dbg_height/dbg_decimate;
while (dbg_owidth < 40) {
dbg_decimate /= 2;
dbg_owidth = dbg_width/dbg_decimate;
dbg_oheight = dbg_height/dbg_decimate;
}
int dbg_length = dbg_owidth*dbg_oheight;
String [] dbg_titles_sym= {"sym0","sym1","sym2","sym3","sym4","sym5","sroll0","sroll1","sroll2","sroll3", "zoom0", "zoom1", "zoom2"};
String [] dbg_titles_xy= {"dx0","dy0","dx1","dy1","dx2","dy2","dx3","y3"};
......
src/main/java/com/elphel/imagej/tileprocessor/Correlation2d.java
View file @ 6c2fb8a0
......@@ -244,6 +244,7 @@ public class Correlation2d {
* @param clt_data1 [3][4][transform_len] first operand data. First index - RBG color
* @param clt_data2 [3][4][transform_len] first operand data. First index - RBG color
* @param lpf optional [transform_len] LPF filter data
* @param scale_value scale correlation results to compensate for lpf changes and other factors
* @param col_weights [3] - color weights {R, B, G} - green is last, normalized to sum =1.0
* @param fat_zero fat zero for phase correlation (0 seems to be OK)
* @return correlation result [(2*transform_size-1) * (2*transform_size-1)]
......@@ -252,6 +253,7 @@ public class Correlation2d {
double [][][] clt_data1,
double [][][] clt_data2,
double [] lpf,
double scale_value, // scale correlation value
double [] col_weights_in, // should have the same dimension as clt_data1 and clt_data2
double fat_zero) {
......@@ -266,13 +268,18 @@ public class Correlation2d {
s+=col_weights[i];
}
for (int i = 0; i < col_weights.length; i++) {
if (col_weights[i] != 0.0) col_weights[i]/=s; // will have 1.0 for the single color
if (col_weights[i] != 0.0) col_weights[i] *= scale_value;
}
if (clt_data1.length == 1) { // monochrome
col_weights = new double[1];
col_weights[0] = 1.0;
}
for (int i = 0; i < col_weights.length; i++) {
if (col_weights[i] != 0.0) col_weights[i]/=s; // will have 1.0 for the single color
}
double [][][]tcorr = new double [clt_data1.length][4][transform_len];
int first_col = -1;
for (int col = 0; col < tcorr.length; col++) if (col_weights[col] > 0.0 ) {
......@@ -280,7 +287,7 @@ public class Correlation2d {
clt_data1[col],
clt_data2[col],
tcorr[col],
fat_zero);
fat_zero/scale_value);
if (first_col < 0) {// accummulate all channels in frst non-null color ( 0 for color, 2 for mono?)
first_col = col; // first non-empty color (2, green) or 0 for color images
......@@ -320,6 +327,7 @@ public class Correlation2d {
* @param tileY tile to extract Y index
* @param pairs_mask bimask of required pairs
* @param lpf optional low-pass filter
* @param scale_value scale correlation results to compensate for lpf changes and other factors
* @param col_weights RBG color weights
* @param fat_zero fat zero for phase correlations
* @return [pair][corr_index]
......@@ -330,6 +338,7 @@ public class Correlation2d {
int tileY,
int pairs_mask,
double [] lpf,
double scale_value, // scale correlation value
double [] col_weights,
double fat_zero) {
double [][][][] clt_data_tile = new double[clt_data.length][][][];
......@@ -343,6 +352,7 @@ public class Correlation2d {
clt_data_tile,
pairs_mask, // already decoded so bit 0 - pair 0
lpf,
scale_value,
col_weights,
fat_zero);
}
......@@ -352,6 +362,7 @@ public class Correlation2d {
* @param clt_data aberration-corrected FD CLT data for one tile [camera][color][quadrant][index]
* @param pairs_mask bimask of required pairs
* @param lpf optional low-pass filter
* @param scale_value scale correlation results to compensate for lpf changes and other factors
* @param col_weights RBG color weights
* @param fat_zero fat zero for phase correlations
* @return [pair][corr_index]
......@@ -360,6 +371,7 @@ public class Correlation2d {
double [][][][] clt_data_tile,
int pairs_mask, // already decoded so bit 0 - pair 0
double [] lpf,
double scale_value, // scale correlation value
double [] col_weights,
double fat_zero) {
if (clt_data_tile == null) return null;
......@@ -372,6 +384,7 @@ public class Correlation2d {
clt_data_tile[ncam1], // double [][][] clt_data1,
clt_data_tile[ncam2], // double [][][] clt_data2,
lpf, // double [] lpf,
scale_value,
col_weights, // double [] col_weights,
fat_zero); // double fat_zero)
}
......@@ -385,6 +398,7 @@ public class Correlation2d {
* @param clt_data_tile_main aberration-corrected FD CLT data for one tile of the main quad camera [sub-camera][color][quadrant][index]
* @param clt_data_tile_aux aberration-corrected FD CLT data for one tile of the auxiliary quad camera [sub-camera][color][quadrant][index]
* @param lpf optional low-pass filter
* @param scale_value scale correlation results to compensate for lpf changes and other factors
* @param col_weights RBG color weights
* @param fat_zero fat zero for phase correlations
* @return 2-d correlation array in line scan order
......@@ -393,6 +407,7 @@ public class Correlation2d {
double [][][][] clt_data_tile_main,
double [][][][] clt_data_tile_aux,
double [] lpf,
double scale_value, // scale correlation value
double [] col_weights,
double fat_zero) {
if ((clt_data_tile_main == null) || (clt_data_tile_aux == null)) return null;
......@@ -402,6 +417,7 @@ public class Correlation2d {
clt_mix_main, // double [][][] clt_data1,
clt_mix_aux, // double [][][] clt_data2,
lpf, // double [] lpf,
scale_value, // scale correlation value
col_weights, // double [] col_weights,
fat_zero); // double fat_zero)
return inter_cam_corr;
......
src/main/java/com/elphel/imagej/tileprocessor/GeometryCorrection.java
View file @ 6c2fb8a0
......@@ -1340,8 +1340,8 @@ public class GeometryCorrection {
sv[i] = sym_vect[i]*1000.0*distortionRadius/pixelSize; // zooms
}
s = String.format("tilt (up): %8.5fpx %8.5fpx %8.5fpx %8.5fpx (shift of he image center)\n" , v[0], v[1], v[2], -(v[0] + v[1] + v[2]) );
s += String.format("azimuth (right): %8.5fpx %8.5fpx %8.5fpx %8.5fpx (shift of he image center)\n" , v[3], v[4], v[5], -(v[3] + v[4] + v[5]) );
s = String.format("tilt (up): %8.5fpx %8.5fpx %8.5fpx %8.5fpx (shift of the image center)\n" , v[0], v[1], v[2], -(v[0] + v[1] + v[2]) );
s += String.format("azimuth (right): %8.5fpx %8.5fpx %8.5fpx %8.5fpx (shift of the image center)\n" , v[3], v[4], v[5], -(v[3] + v[4] + v[5]) );
s += String.format("roll (CW): %8.5fpx %8.5fpx %8.5fpx %8.5fpx (shift at the image half-width from the center)\n" , v[6], v[7], v[8], v[9] );
s += String.format("diff zoom (in): %8.5fpx %8.5fpx %8.5fpx %8.5fpx (shift at the image half-width from the center)\n" , v[10], v[11], v[12], -(v[10] + v[11] + v[12]) );
s += "Symmetrical vector:\n";
......
src/main/java/com/elphel/imagej/tileprocessor/ImageDtt.java
View file @ 6c2fb8a0
......@@ -202,6 +202,7 @@ public class ImageDtt {
static String [] TCORR_TITLES = {"combo","sum","hor","vert"};
private final boolean monochrome;
private final double scale_strengths; // scale all correlation strengths (to compensate for LPF sigma changes)
public static int getImgMask (int data){ return (data & 0xf);} // which images to use
......@@ -213,8 +214,11 @@ public class ImageDtt {
public static boolean getOrthoLines (int data){return (data & 0x200) != 0;}
public static int setOrthoLines (int data, boolean force) {return (data & ~0x200) | (force?0x200:0);}
public ImageDtt(boolean mono){
monochrome = mono;
public ImageDtt(
boolean mono,
double scale_strengths){
this.monochrome = mono;
this.scale_strengths = scale_strengths;
}
public boolean isMonochrome() {
......@@ -2110,14 +2114,16 @@ public class ImageDtt {
// calculate all selected pairs correlations
int all_pairs = imgdtt_params.dbg_pair_mask; //TODO: use tile tasks
double [][] corrs = corr2d.correlateCompositeFD( // now works with nulls for some clt_data colors
clt_data, // double [][][][][][] clt_data,
tileX, // int tileX,
tileY, // int tileY,
all_pairs, // int pairs_mask,
filter, // double [] lpf,
col_weights, // double [] col_weights,
corr_fat_zero); // double fat_zero)
double [][] corrs = corr2d.correlateCompositeFD( // now works with nulls for some clt_data colors
clt_data, // double [][][][][][] clt_data,
tileX, // int tileX,
tileY, // int tileY,
all_pairs, // int pairs_mask,
filter, // double [] lpf,
scale_strengths, // 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 -
......@@ -2233,8 +2239,8 @@ public class ImageDtt {
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];
disparity_map[DISPARITY_INDEX_HOR][tIndex] = -hor_pair1[0];
disparity_map[DISPARITY_INDEX_HOR_STRENGTH][tIndex] = hor_pair1[1];
}
double [] vert_pair1 = corr2d.getMaxXSOrtho(
......@@ -6208,7 +6214,7 @@ public class ImageDtt {
// Create window to select center correlation strip using
// ortho_height - full width of non-zero elements
// ortho_eff_height - effective height (ration of the weighted column sum to the center value)
// ortho_eff_height - effective height (ratio of the weighted column sum to the center value)
int wcenter = transform_size - 1;
final double [] ortho_weights = new double [corr_size]; // [15]
for (int i = 0; i < corr_size; i++){
......@@ -7372,6 +7378,7 @@ public class ImageDtt {
clt_data_tile_main, // double [][][][] clt_data_tile_main,
clt_data_tile_aux, // double [][][][] clt_data_tile_aux,
filter, // double [] lpf,
scale_strengths,
col_weights, // double [] col_weights,
fatzero); // double fat_zero)
......@@ -7627,6 +7634,7 @@ public class ImageDtt {
clt_data, // double [][][][] clt_data, // aberration-corrected FD CLT data for one tile [camera][color][quadrant][index]
all_pairs, // int pairs_mask,
filter, // double [] lpf,
scale_strengths,
col_weights, // double [] col_weights,
fatzero); // double fat_zero)
......@@ -8466,6 +8474,7 @@ public class ImageDtt {
clt_data_main, // double [][][][] clt_data_tile_main,
clt_data_aux, // double [][][][] clt_data_tile_aux,
filter, // double [] lpf,
scale_strengths,
col_weights, // double [] col_weights,
fatzero); // double fat_zero)
......@@ -9242,6 +9251,7 @@ public class ImageDtt {
clt_data_main, // double [][][][] clt_data_tile_main,
clt_data_aux, // double [][][][] clt_data_tile_aux,
filter, // double [] lpf,
scale_strengths,
col_weights, // double [] col_weights,
fatzero); // double fat_zero)
......@@ -9630,7 +9640,7 @@ public class ImageDtt {
System.out.println("max_corr_radius= "+clt_parameters.max_corr_radius);
System.out.println("max_search_radius= "+max_search_radius);
System.out.println("max_search_radius_poly="+max_search_radius_poly);
System.out.println("corr_fat_zero= "+clt_parameters.fat_zero);
System.out.println("corr_fat_zero= "+clt_parameters.getFatZero(isMonochrome()));
System.out.println("disparity_array[0][0]= "+disparity_array[0][0]);
......
src/main/java/com/elphel/imagej/tileprocessor/MacroCorrelation.java
View file @ 6c2fb8a0
......@@ -63,6 +63,7 @@ public class MacroCorrelation {
tileSize, // int tileSize,
tp.superTileSize, // int superTileSize,
tp.isMonochrome(),
tp.isAux(),
tp.getMagicScale(), // double scale,
trusted_correlation, // double trustedCorrelation,
0.0, // double maxOverexposure,
......@@ -305,7 +306,9 @@ public class MacroCorrelation {
// double [][][][] texture_tiles = save_textures ? new double [tilesY][tilesX][][] : null; // ["RGBA".length()][];
ImageDtt image_dtt = new ImageDtt(this.mtp.isMonochrome());
ImageDtt image_dtt = new ImageDtt(
this.mtp.isMonochrome(),
clt_parameters.getScaleStrength(this.mtp.isAux()));
image_dtt.clt_aberrations_quad_corr(
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
8, // final int macro_scale, // to correlate tile data instead of the pixel data: 1 - pixels, 8 - tiles
......@@ -321,7 +324,7 @@ public class MacroCorrelation {
disparity_map, // [12][tp.tilesY * tp.tilesX]
null, // [tp.tilesY][tp.tilesX]["RGBA".length()][];
mTilesX * clt_parameters.transform_size, // imp_quad[0].getWidth(), // final int width,
clt_parameters.fat_zero, // add to denominator to modify phase correlation (same units as data1, data2). <0 - pure sum
clt_parameters.getFatZero(image_dtt.isMonochrome()), // add to denominator to modify phase correlation (same units as data1, data2). <0 - pure sum
clt_parameters.corr_sym,
clt_parameters.corr_offset,
clt_parameters.corr_red,
......
src/main/java/com/elphel/imagej/tileprocessor/PoleProcessor.java
View file @ 6c2fb8a0
......@@ -2723,7 +2723,7 @@ public class PoleProcessor {
disparity_array, // double [][] disparity_array,
null, // double [][] ml_data, // data for ML - 10 layers - 4 center areas (3x3, 5x5,..) per camera-per direction, 1 - composite, and 1 with just 1 data (target disparity)
clt_parameters, // EyesisCorrectionParameters.CLTParameters clt_parameters,
clt_parameters.fat_zero, // double fatzero,
clt_parameters.getFatZero(quadCLT_main.isMonochrome()), // double fatzero,
notch_mode, // final boolean notch_mode, // use notch filter for inter-camera correlation to detect poles
lt_rad, // final int // low texture mode - inter-correlation is averaged between the neighbors before argmax-ing, using
true, // boolean no_int_x0, // do not offset window to integer maximum - used when averaging low textures to avoid "jumps" for very wide
......
src/main/java/com/elphel/imagej/tileprocessor/TileProcessor.java
View file @ 6c2fb8a0
......@@ -75,6 +75,7 @@ public class TileProcessor {
public double [][] main_ds_ml = null; // main camera DSI restored from the COMBO-DSI file to generate ML test files
public boolean monochrome = false; // these are monochrome images
private boolean is_aux = false; // this camera is aux
public int clt_3d_passes_size = 0; //clt_3d_passes size after initial processing
public int clt_3d_passes_rig_size = 0; //clt_3d_passes size after initial processing and rig processing
private int tilesX;
......@@ -104,6 +105,7 @@ public class TileProcessor {
int tileSize,
int superTileSize,
boolean monochrome,
boolean is_aux,
double scale,
double trustedCorrelation,
double maxOverexposure,
......@@ -114,12 +116,15 @@ public class TileProcessor {
this.tileSize = tileSize;
this.superTileSize = superTileSize;
this.monochrome = monochrome;
this.is_aux = is_aux;
this.corr_magic_scale = scale;
this.trustedCorrelation = trustedCorrelation;
this.maxOverexposure = maxOverexposure;
this.threadsMax = threadsMax;
}
public boolean isMonochrome() {return monochrome;}
public boolean isAux() {return is_aux;}
public int getTilesX() {return tilesX;}
public int getTilesY() {return tilesY;}
public int getTileSize() {return tileSize;}
......@@ -3055,7 +3060,7 @@ public class TileProcessor {
dbg_img[3][i] = disparity_map[ImageDtt.DISPARITY_STRENGTH_INDEX][i];
dbg_img[4][i] = disparity_map[disparity_index][i];
}
sdfa_instance.showArrays(dbg_img, tilesX, tilesY, true, "bgnd_nonbgnd",titles);
sdfa_instance.showArrays(dbg_img, tilesX, tilesY, true, "bgnd_nonbgnd_new",titles);
}
for (int gain = 1; gain > 0;){
......@@ -4062,19 +4067,53 @@ public class TileProcessor {
}
public int [][] setSameTileOp(
int op){
return setSameTileOp(
0,
tilesX,
0,
tilesY,
op,
-1);
}
public int [][] setSameTileOp(
CLTParameters clt_parameters,
int op,
int debugLevel
)
{
int [][] tile_op = new int [tilesY][tilesX]; // all zero
int debugLevel){
int txl = clt_parameters.tile_task_wl;
int txr = txl + clt_parameters.tile_task_ww;
int tyt = clt_parameters.tile_task_wt;
int tyb = tyt + clt_parameters.tile_task_wh;
if (debugLevel > -1){
System.out.println("clt_parameters.tile_task_wl="+clt_parameters.tile_task_wl );
System.out.println("clt_parameters.tile_task_wt="+clt_parameters.tile_task_wt );
System.out.println("clt_parameters.tile_task_ww="+clt_parameters.tile_task_ww );
System.out.println("clt_parameters.tile_task_wh="+clt_parameters.tile_task_wh );
}
return setSameTileOp(
txl,
txr,
tyt,
tyb,
op,
debugLevel);
}
public int [][] setSameTileOp(
// CLTParameters clt_parameters,
int txl, // = clt_parameters.tile_task_wl;
int txr, // = txl + clt_parameters.tile_task_ww;
int tyt, // = clt_parameters.tile_task_wt;
int tyb, // = tyt + clt_parameters.tile_task_wh;
int op,
int debugLevel
)
{
int [][] tile_op = new int [tilesY][tilesX]; // all zero
if (txl < 0) txl = 0;
else if (txl >= tilesX) txl = tilesX - 1;
......@@ -4093,10 +4132,6 @@ public class TileProcessor {
}
}
if (debugLevel > -1){
System.out.println("clt_parameters.tile_task_wl="+clt_parameters.tile_task_wl );
System.out.println("clt_parameters.tile_task_wt="+clt_parameters.tile_task_wt );
System.out.println("clt_parameters.tile_task_ww="+clt_parameters.tile_task_ww );
System.out.println("clt_parameters.tile_task_wh="+clt_parameters.tile_task_wh );
System.out.println("getImgMask("+op+")="+ImageDtt.getImgMask(op) );
System.out.println("getPairMask("+op+")="+ImageDtt.getPairMask(op) );
System.out.println("getForcedDisparity("+op+")="+ImageDtt.getForcedDisparity(op) );
......@@ -5165,12 +5200,11 @@ public class TileProcessor {
public double [][] assignTilesToSurfaces(
CLTParameters clt_parameters,
CLTParameters clt_parameters,
GeometryCorrection geometryCorrection,
final int threadsMax, // maximal number of threads to launch
final boolean updateStatus,
// final boolean batch_mode,
final int debugLevel)
final int threadsMax, // maximal number of threads to launch
final boolean updateStatus,
final int debugLevel)
{
final boolean batch_mode = clt_parameters.batch_run;
final int debugLevelInner = batch_mode ? -5: debugLevel;
......@@ -5185,7 +5219,7 @@ public class TileProcessor {
// show testure_tiles
double [][][][] texture_tiles = scan_prev.getTextureTiles();
ImageDtt image_dtt = new ImageDtt(isMonochrome());
ImageDtt image_dtt = new ImageDtt(isMonochrome(), clt_parameters.getScaleStrength(is_aux));
double [][][] dispStrength = st.getDisparityStrengths(
clt_parameters.stMeasSel); // int stMeasSel) // = 1; // Select measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert)
......
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