Commit 27498290 authored by Andrey Filippov's avatar Andrey Filippov

Low texture areas - debugging averaging correlation with surface

approximation with planes
parent 58970e5a
...@@ -156,11 +156,12 @@ public class BiQuadParameters { ...@@ -156,11 +156,12 @@ public class BiQuadParameters {
// filtering lt candidates // filtering lt candidates
public double ltavg_min_disparity = -1.0; // any public double ltavg_min_disparity = -1.0; // any
public double ltavg_max_density = 0.1; public double ltavg_max_density = 0.1;
public int ltavg_grow = 4; // each 2 add 8 directions step. Odd have last step in 4 ortho directions only. public int ltavg_gap_hwidth = 2; // maximal radius of a void to be filled
public int ltavg_shrink = 2; // shrink after expanding. Combination of both fills small gaps public int ltavg_clust_hwidth = 5; // minimal radius of a cluster to keep
public int ltavg_extra_grow = 1; // additionally grow low-textured areas selections
// smoothing parameters // smoothing parameters
public boolean ltavg_smooth_strength = false; // provide tile strength when smoothing target disparity public boolean ltavg_smooth_strength = false; // provide tile strength when smoothing target disparity
public double ltavg_neib_pull = 0.2; // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s public double ltavg_neib_pull = 1.0; // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s
public int ltavg_max_iter = 20; // public int ltavg_max_iter = 20; //
public double ltavg_min_change = 0.01; // public double ltavg_min_change = 0.01; //
...@@ -461,10 +462,12 @@ public class BiQuadParameters { ...@@ -461,10 +462,12 @@ public class BiQuadParameters {
"May be used to mask out infinity background"); "May be used to mask out infinity background");
gd.addNumericField("Maximal density to consider it to be low textured area", this.ltavg_max_density, 4,6,"", gd.addNumericField("Maximal density to consider it to be low textured area", this.ltavg_max_density, 4,6,"",
"Select areas with lower density"); "Select areas with lower density");
gd.addNumericField("Grow selection, each two units get expanion in 8 directions", this.ltavg_grow, 0,3,"", gd.addNumericField("Maximal radius of a void in low-texture selection to fill" , this.ltavg_gap_hwidth, 0,3,"",
"Two steps give one-tile expansion in 8 directions, odd numbers expand only in 4 ortho directions on the last expansion"); "Low textured selection may have gaps that will be filled");
gd.addNumericField("Shrink selection after growing", this.ltavg_shrink, 0,3,"", gd.addNumericField("Minimal radius of a low-textured cluster to process", this.ltavg_clust_hwidth, 0,3,"",
"Grow followed by shring fill small gaps"); "Remove low-textured areas smaller that twice this size in each orthogonal directions");
gd.addNumericField("Additionally grow low-textured areas selections", this.ltavg_extra_grow, 0,3,"",
"Low textured areas will be grown by the radius of correlation averaging plus this value");
gd.addCheckbox ("Use tile strengths when filling gaps/smoothing", this.ltavg_smooth_strength, gd.addCheckbox ("Use tile strengths when filling gaps/smoothing", this.ltavg_smooth_strength,
"Unchecked - consider all tiles to have the same strength"); "Unchecked - consider all tiles to have the same strength");
gd.addNumericField("Relative pull of the nieghbor tiles compared to the original disparity" , this.ltavg_neib_pull, 4,6,"", gd.addNumericField("Relative pull of the nieghbor tiles compared to the original disparity" , this.ltavg_neib_pull, 4,6,"",
...@@ -678,8 +681,9 @@ public class BiQuadParameters { ...@@ -678,8 +681,9 @@ public class BiQuadParameters {
this.ltavg_dens_radius= (int) gd.getNextNumber(); this.ltavg_dens_radius= (int) gd.getNextNumber();
this.ltavg_min_disparity= gd.getNextNumber(); this.ltavg_min_disparity= gd.getNextNumber();
this.ltavg_max_density= gd.getNextNumber(); this.ltavg_max_density= gd.getNextNumber();
this.ltavg_grow= (int) gd.getNextNumber(); this.ltavg_gap_hwidth= (int) gd.getNextNumber();
this.ltavg_shrink= (int) gd.getNextNumber(); this.ltavg_clust_hwidth= (int) gd.getNextNumber();
this.ltavg_extra_grow= (int) gd.getNextNumber();
this.ltavg_smooth_strength= gd.getNextBoolean(); this.ltavg_smooth_strength= gd.getNextBoolean();
this.ltavg_neib_pull= gd.getNextNumber(); this.ltavg_neib_pull= gd.getNextNumber();
this.ltavg_max_iter= (int) gd.getNextNumber(); this.ltavg_max_iter= (int) gd.getNextNumber();
...@@ -846,8 +850,10 @@ public class BiQuadParameters { ...@@ -846,8 +850,10 @@ public class BiQuadParameters {
properties.setProperty(prefix+"ltavg_dens_radius", this.ltavg_dens_radius+""); properties.setProperty(prefix+"ltavg_dens_radius", this.ltavg_dens_radius+"");
properties.setProperty(prefix+"ltavg_min_disparity", this.ltavg_min_disparity+""); properties.setProperty(prefix+"ltavg_min_disparity", this.ltavg_min_disparity+"");
properties.setProperty(prefix+"ltavg_max_density", this.ltavg_max_density+""); properties.setProperty(prefix+"ltavg_max_density", this.ltavg_max_density+"");
properties.setProperty(prefix+"ltavg_grow", this.ltavg_grow+""); properties.setProperty(prefix+"ltavg_gap_hwidth", this.ltavg_gap_hwidth+"");
properties.setProperty(prefix+"ltavg_shrink", this.ltavg_shrink+""); properties.setProperty(prefix+"ltavg_clust_hwidth", this.ltavg_clust_hwidth+"");
properties.setProperty(prefix+"ltavg_extra_grow", this.ltavg_extra_grow+"");
properties.setProperty(prefix+"ltavg_smooth_strength", this.ltavg_smooth_strength+""); properties.setProperty(prefix+"ltavg_smooth_strength", this.ltavg_smooth_strength+"");
properties.setProperty(prefix+"ltavg_neib_pull", this.ltavg_neib_pull+""); properties.setProperty(prefix+"ltavg_neib_pull", this.ltavg_neib_pull+"");
properties.setProperty(prefix+"ltavg_max_iter", this.ltavg_max_iter+""); properties.setProperty(prefix+"ltavg_max_iter", this.ltavg_max_iter+"");
...@@ -1015,8 +1021,10 @@ public class BiQuadParameters { ...@@ -1015,8 +1021,10 @@ public class BiQuadParameters {
if (properties.getProperty(prefix+"ltavg_dens_radius")!=null) this.ltavg_dens_radius=Integer.parseInt(properties.getProperty(prefix+"ltavg_dens_radius")); if (properties.getProperty(prefix+"ltavg_dens_radius")!=null) this.ltavg_dens_radius=Integer.parseInt(properties.getProperty(prefix+"ltavg_dens_radius"));
if (properties.getProperty(prefix+"ltavg_min_disparity")!=null) this.ltavg_min_disparity=Double.parseDouble(properties.getProperty(prefix+"ltavg_min_disparity")); if (properties.getProperty(prefix+"ltavg_min_disparity")!=null) this.ltavg_min_disparity=Double.parseDouble(properties.getProperty(prefix+"ltavg_min_disparity"));
if (properties.getProperty(prefix+"ltavg_max_density")!=null) this.ltavg_max_density=Double.parseDouble(properties.getProperty(prefix+"ltavg_max_density")); if (properties.getProperty(prefix+"ltavg_max_density")!=null) this.ltavg_max_density=Double.parseDouble(properties.getProperty(prefix+"ltavg_max_density"));
if (properties.getProperty(prefix+"ltavg_grow")!=null) this.ltavg_grow=Integer.parseInt(properties.getProperty(prefix+"ltavg_grow")); if (properties.getProperty(prefix+"ltavg_gap_hwidth")!=null) this.ltavg_gap_hwidth=Integer.parseInt(properties.getProperty(prefix+"ltavg_gap_hwidth"));
if (properties.getProperty(prefix+"ltavg_shrink")!=null) this.ltavg_shrink=Integer.parseInt(properties.getProperty(prefix+"ltavg_shrink")); if (properties.getProperty(prefix+"ltavg_clust_hwidth")!=null) this.ltavg_clust_hwidth=Integer.parseInt(properties.getProperty(prefix+"ltavg_clust_hwidth"));
if (properties.getProperty(prefix+"ltavg_extra_grow")!=null) this.ltavg_extra_grow=Integer.parseInt(properties.getProperty(prefix+"ltavg_extra_grow"));
if (properties.getProperty(prefix+"ltavg_smooth_strength")!=null) this.ltavg_smooth_strength=Boolean.parseBoolean(properties.getProperty(prefix+"ltavg_smooth_strength")); if (properties.getProperty(prefix+"ltavg_smooth_strength")!=null) this.ltavg_smooth_strength=Boolean.parseBoolean(properties.getProperty(prefix+"ltavg_smooth_strength"));
if (properties.getProperty(prefix+"ltavg_neib_pull")!=null) this.ltavg_neib_pull=Double.parseDouble(properties.getProperty(prefix+"ltavg_neib_pull")); if (properties.getProperty(prefix+"ltavg_neib_pull")!=null) this.ltavg_neib_pull=Double.parseDouble(properties.getProperty(prefix+"ltavg_neib_pull"));
if (properties.getProperty(prefix+"ltavg_max_iter")!=null) this.ltavg_max_iter=Integer.parseInt(properties.getProperty(prefix+"ltavg_max_iter")); if (properties.getProperty(prefix+"ltavg_max_iter")!=null) this.ltavg_max_iter=Integer.parseInt(properties.getProperty(prefix+"ltavg_max_iter"));
...@@ -1182,8 +1190,9 @@ public class BiQuadParameters { ...@@ -1182,8 +1190,9 @@ public class BiQuadParameters {
bqp.ltavg_dens_radius= this.ltavg_dens_radius; bqp.ltavg_dens_radius= this.ltavg_dens_radius;
bqp.ltavg_min_disparity= this.ltavg_min_disparity; bqp.ltavg_min_disparity= this.ltavg_min_disparity;
bqp.ltavg_max_density= this.ltavg_max_density; bqp.ltavg_max_density= this.ltavg_max_density;
bqp.ltavg_grow= this.ltavg_grow; bqp.ltavg_gap_hwidth= this.ltavg_gap_hwidth;
bqp.ltavg_shrink= this.ltavg_shrink; bqp.ltavg_clust_hwidth= this.ltavg_clust_hwidth;
bqp.ltavg_extra_grow= this.ltavg_extra_grow;
bqp.ltavg_smooth_strength= this.ltavg_smooth_strength; bqp.ltavg_smooth_strength= this.ltavg_smooth_strength;
bqp.ltavg_neib_pull= this.ltavg_neib_pull; bqp.ltavg_neib_pull= this.ltavg_neib_pull;
bqp.ltavg_max_iter= this.ltavg_max_iter; bqp.ltavg_max_iter= this.ltavg_max_iter;
......
...@@ -150,6 +150,7 @@ public class BiScan { ...@@ -150,6 +150,7 @@ public class BiScan {
// trusted should be set, copied and replaced as needed // trusted should be set, copied and replaced as needed
public double [][] getFilteredDisparityStrength( // FIXME public double [][] getFilteredDisparityStrength( // FIXME
final boolean [] area_of_interest,
final double [][] disparityStrength, final double [][] disparityStrength,
final double min_disparity, // keep original disparity far tiles final double min_disparity, // keep original disparity far tiles
final double trusted_strength, // trusted correlation strength final double trusted_strength, // trusted correlation strength
...@@ -193,6 +194,7 @@ public class BiScan { ...@@ -193,6 +194,7 @@ public class BiScan {
for (int i = 0; i < num_tiles; i++) ds[0][i] = Double.NaN; for (int i = 0; i < num_tiles; i++) ds[0][i] = Double.NaN;
// double boost_low_density = 0.8; // 1.0; //0.2; // double boost_low_density = 0.8; // 1.0; //0.2;
suggestNewScan( suggestNewScan(
area_of_interest, // final boolean [] area_of_interest,
disparityStrength, // final double [][] disparityStrength, disparityStrength, // final double [][] disparityStrength,
trusted_strength, // final double trusted_strength, // trusted correlation strength trusted_strength, // final double trusted_strength, // trusted correlation strength
strength_rfloor, // final double strength_rfloor, // strength floor - relative to trusted strength_rfloor, // final double strength_rfloor, // strength floor - relative to trusted
...@@ -480,14 +482,15 @@ public class BiScan { ...@@ -480,14 +482,15 @@ public class BiScan {
* 2) target disaprity that lead to the current measurement after refinement * 2) target disaprity that lead to the current measurement after refinement
* 3) any other disable measurement * 3) any other disable measurement
* 4) any target disparity that lead to the disabled measurement * 4) any target disparity that lead to the disabled measurement
* @param area_of_interest - limit results to these tiles (if provided)
* @param disparityStrength - a pair of array or null. If null, will calculate fro the current scan * @param disparityStrength - a pair of array or null. If null, will calculate fro the current scan
* if not null - use as is * if not null - use as is
* @param trusted_strength strength to trust unconditionally * @param trusted_strength strength to trust unconditionally
* @param strength_rfloor strength floor to subrtact as a fraction of the trusted strength * @param strength_rfloor strength floor to subtract as a fraction of the trusted strength
* @param discard_cond if true may suggest new disparities for conditionally trusted tiles * @param discard_cond if true may suggest new disparities for conditionally trusted tiles
* @param discard_weak if true may suggest new disparities over trusted weak tiles * @param discard_weak if true may suggest new disparities over trusted weak tiles
* @param discard_stron if true may suggest new disparities over any tile * @param discard_stron if true may suggest new disparities over any tile
* @param strength_pow raise strength to thyis power (normally just 1.0) * @param strength_pow raise strength to this power (normally just 1.0)
* @param smpl_radius sample "radius", square side is 2 * smpl_radius + 1 * @param smpl_radius sample "radius", square side is 2 * smpl_radius + 1
* @param smpl_num minimal absolute number of samples required to try fit a plane and validate a tile * @param smpl_num minimal absolute number of samples required to try fit a plane and validate a tile
* If smpl_num == 0, faster calculation (single pass) using only *_narrow settings * If smpl_num == 0, faster calculation (single pass) using only *_narrow settings
...@@ -501,7 +504,7 @@ public class BiScan { ...@@ -501,7 +504,7 @@ public class BiScan {
* @param smpl_rrms maximal relative (additional)rms of the weighted remaining samples for the successful plane fitting * @param smpl_rrms maximal relative (additional)rms of the weighted remaining samples for the successful plane fitting
* @param damp_tilt regularization value to handle planes if the remaining samples are co-linear (or just a single tile) * @param damp_tilt regularization value to handle planes if the remaining samples are co-linear (or just a single tile)
* @param rwsigma weight Gaussian sigma to reduce influence of far tiles relative to smpl_radius * @param rwsigma weight Gaussian sigma to reduce influence of far tiles relative to smpl_radius
* @param rwsigma_narrow Gaussian sigma for the preliminary plain fitting using the closesttiles ~= 1/smpl_radius * @param rwsigma_narrow Gaussian sigma for the preliminary plain fitting using the closest tiles ~= 1/smpl_radius
* @param new_diff minimal difference between the new suggested and the already tried/measured one * @param new_diff minimal difference between the new suggested and the already tried/measured one
* @param remove_all_tried remove from suggested - not only disabled, but all tried * @param remove_all_tried remove from suggested - not only disabled, but all tried
* @param center_weight weight of the tile itself (0.0 - do not use). Should be set to 0.0 for suggesting, >0 - for "smoothing" * @param center_weight weight of the tile itself (0.0 - do not use). Should be set to 0.0 for suggesting, >0 - for "smoothing"
...@@ -519,6 +522,7 @@ public class BiScan { ...@@ -519,6 +522,7 @@ public class BiScan {
*/ */
int suggestNewScan( int suggestNewScan(
final boolean [] area_of_interest,
final double [][] disparityStrength, final double [][] disparityStrength,
final double trusted_strength, // trusted correlation strength final double trusted_strength, // trusted correlation strength
final double strength_rfloor, // strength floor - relative to trusted final double strength_rfloor, // strength floor - relative to trusted
...@@ -545,7 +549,7 @@ public class BiScan { ...@@ -545,7 +549,7 @@ public class BiScan {
final boolean use_alt, // use tiles from other scans if they fit better final boolean use_alt, // use tiles from other scans if they fit better
final double goal_fraction_rms, // Try to make rms to be this fraction of maximal acceptable by removing outliers final double goal_fraction_rms, // Try to make rms to be this fraction of maximal acceptable by removing outliers
final double boost_low_density, // 0 - strength is proportional to 1/density, 1.0 - same as remaining tiles final double boost_low_density, // 0 - strength is proportional to 1/density, 1.0 - same as remaining tiles
final double [][] smooth_ds, // optionally fill disaprity/strength instead of the target_disparity final double [][] smooth_ds, // optionally fill disparity/strength instead of the target_disparity
final int fourq_min, // each of the 4 corners should have at least this number of tiles. final int fourq_min, // each of the 4 corners should have at least this number of tiles.
final int fourq_gap, // symmetrical vertical and horizontal center areas that do not belong to any corner final int fourq_gap, // symmetrical vertical and horizontal center areas that do not belong to any corner
final int dbg_x, final int dbg_x,
...@@ -627,7 +631,8 @@ public class BiScan { ...@@ -627,7 +631,8 @@ public class BiScan {
threads[ithread] = new Thread() { threads[ithread] = new Thread() {
@Override @Override
public void run() { public void run() {
for (int nTile = ai.getAndIncrement(); nTile < num_tiles; nTile = ai.getAndIncrement()) if (discard_strong || !trusted_sw[nTile]){ for (int nTile = ai.getAndIncrement(); nTile < num_tiles; nTile = ai.getAndIncrement()) if (
((area_of_interest == null) || area_of_interest[nTile]) && (discard_strong || !trusted_sw[nTile])){
boolean debug = nTile == dbg_tile; boolean debug = nTile == dbg_tile;
if (debug) { if (debug) {
System.out.println("suggestNewScan(): debbugging nTile="+nTile); System.out.println("suggestNewScan(): debbugging nTile="+nTile);
...@@ -864,6 +869,8 @@ public class BiScan { ...@@ -864,6 +869,8 @@ public class BiScan {
return num_new.get(); return num_new.get();
} }
private int findBetterFitToPlane( private int findBetterFitToPlane(
int smpl_radius, int smpl_radius,
int nTile, int nTile,
...@@ -1948,32 +1955,49 @@ public class BiScan { ...@@ -1948,32 +1955,49 @@ public class BiScan {
* Select low-textured tiles for averaging measurements * Select low-textured tiles for averaging measurements
* @param min_disparity minimal disparity to accept * @param min_disparity minimal disparity to accept
* @param max_density maximal trusted tile density (density varies from 0.0 to 1.0) * @param max_density maximal trusted tile density (density varies from 0.0 to 1.0)
* @param grow grow selection. When combined with shrink, fills small gaps. Both grow and shrink step * @param grow how many layers of tiles should be added after filling gaps and removing small clusters
* advances either horizontally or vertically (alternating), so to expand by 1 pixel in all directions * @param max_gap_radius maximal radius of a void to be filled
* the value should be set to 2, * @param min_clust_radius minimal original cluster radius to survive
* @param shrink shrink selection after expanding to fill small gaps
* @param density per-tile values of the density of trusted tiles around it. * @param density per-tile values of the density of trusted tiles around it.
* @param src_disparity - source disparity array * @param src_disparity - source disparity array. If null will only use density (that should be > 0)
* @return selection of the low-textured tiles to be processed with averaging correlation (3x3 or 5x5 tiles) * @return selection of the low-textured tiles to be processed with averaging correlation (3x3 or 5x5 tiles)
*/ */
public boolean [] selectLowTextures( public boolean [] selectLowTextures(
double min_disparity, double min_disparity,
double max_density, double max_density,
int grow, int grow,
int shrink, int max_gap_radius,
int min_clust_radius,
double [] density, double [] density,
double [] src_disparity) double [] src_disparity)
{ {
boolean [] selection = new boolean [density.length]; boolean [] selection = new boolean [density.length];
for (int nTile = 0; nTile < selection.length; nTile++) { if (src_disparity == null) {
if ((src_disparity[nTile] >= min_disparity) && (density[nTile] <= max_density)) { // disparity has NaN-s, they will fail comparisons for (int nTile = 0; nTile < selection.length; nTile++) {
selection[nTile] = true; if ((density[nTile] <= max_density) && (density[nTile] <= max_density)) { // disparity has NaN-s, they will fail comparisons
selection[nTile] = true;
}
}
} else {
for (int nTile = 0; nTile < selection.length; nTile++) {
if ((src_disparity[nTile] >= min_disparity) && (density[nTile] <= max_density)) { // disparity has NaN-s, they will fail comparisons
selection[nTile] = true;
}
} }
} }
final TileNeibs tnImage = biCamDSI.tnImage; final TileNeibs tnImage = biCamDSI.tnImage;
tnImage.growSelection( tnImage.growSelection(
grow, // int grow, // grow tile selection by 1 over non-background tiles 1: 4 directions, 2 - 8 directions, 3 - 8 by 1, 4 by 1 more 2* max_gap_radius, // int grow, // grow tile selection by 1 over non-background tiles 1: 4 directions, 2 - 8 directions, 3 - 8 by 1, 4 by 1 more
selection, // boolean [] tiles,
null); // boolean [] prohibit)
tnImage.shrinkSelection(
2*(max_gap_radius + min_clust_radius), // int grow, // grow tile selection by 1 over non-background tiles 1: 4 directions, 2 - 8 directions, 3 - 8 by 1, 4 by 1 more
selection, // boolean [] tiles,
null); // boolean [] prohibit)
tnImage.growSelection(
2 * (min_clust_radius + grow), // int grow, // grow tile selection by 1 over non-background tiles 1: 4 directions, 2 - 8 directions, 3 - 8 by 1, 4 by 1 more
selection, // boolean [] tiles, selection, // boolean [] tiles,
null); // boolean [] prohibit) null); // boolean [] prohibit)
return selection; return selection;
...@@ -2023,6 +2047,7 @@ public class BiScan { ...@@ -2023,6 +2047,7 @@ public class BiScan {
for (int num_iter = 0; num_iter < max_iterations; num_iter++) { for (int num_iter = 0; num_iter < max_iterations; num_iter++) {
ai.set(0); ai.set(0);
ai_numThread.set(0); ai_numThread.set(0);
final AtomicInteger ai_count=new AtomicInteger(0);
for (int i = 0; i < max_changes.length; i++) max_changes[i] = 0.0; for (int i = 0; i < max_changes.length; i++) max_changes[i] = 0.0;
final int fnum_iter = num_iter; final int fnum_iter = num_iter;
for (int ithread = 0; ithread < threads.length; ithread++) { for (int ithread = 0; ithread < threads.length; ithread++) {
...@@ -2070,6 +2095,7 @@ public class BiScan { ...@@ -2070,6 +2095,7 @@ public class BiScan {
new_strength[nTile] = (w_mean * neib_pull + src_strength[nTile])/(neib_pull + 1); new_strength[nTile] = (w_mean * neib_pull + src_strength[nTile])/(neib_pull + 1);
} }
} }
ai_count.getAndIncrement();
double adiff = Math.abs(new_disparity[nTile] - disparity[nTile]); // disparity[nTile] may be NaN then adiff will be NaN as intended double adiff = Math.abs(new_disparity[nTile] - disparity[nTile]); // disparity[nTile] may be NaN then adiff will be NaN as intended
if (!(adiff < max_changes[numThread])) { if (!(adiff < max_changes[numThread])) {
max_changes[numThread] = adiff; // NaN will be copied max_changes[numThread] = adiff; // NaN will be copied
...@@ -2098,7 +2124,7 @@ public class BiScan { ...@@ -2098,7 +2124,7 @@ public class BiScan {
} }
} }
if (debugLevel > -2) { if (debugLevel > -2) {
System.out.println("fillAndSmooth(): iteration "+fnum_iter+" change="+change+" (min_change="+min_change+")"); System.out.println("fillAndSmooth(): iteration "+fnum_iter+" change="+change+" (min_change="+min_change+")+ tiles updated="+ai_count.get());
} }
if (change <= min_change) { // change may be NaN if (change <= min_change) { // change may be NaN
break; // from the main loop break; // from the main loop
......
...@@ -2099,6 +2099,7 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2099,6 +2099,7 @@ if (debugLevel > -100) return true; // temporarily !
*/ */
num_added_tiles = last_scan.suggestNewScan( num_added_tiles = last_scan.suggestNewScan(
null, // final boolean [] area_of_interest,
null, // final double [][] disparityStrength, null, // final double [][] disparityStrength,
clt_parameters.rig.pf_trusted_strength, // final double trusted_strength, // trusted correlation strength clt_parameters.rig.pf_trusted_strength, // final double trusted_strength, // trusted correlation strength
clt_parameters.rig.pf_strength_rfloor, // final double strength_rfloor, // strength floor - relative to trusted clt_parameters.rig.pf_strength_rfloor, // final double strength_rfloor, // strength floor - relative to trusted
...@@ -2198,6 +2199,7 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2198,6 +2199,7 @@ if (debugLevel > -100) return true; // temporarily !
// suggest again, after trimming // suggest again, after trimming
int num_added_tiles_trimmed = last_scan.suggestNewScan( int num_added_tiles_trimmed = last_scan.suggestNewScan(
null, // final boolean [] area_of_interest,
null, // final double [][] disparityStrength, null, // final double [][] disparityStrength,
clt_parameters.rig.pf_trusted_strength, // final double trusted_strength, // trusted correlation strength clt_parameters.rig.pf_trusted_strength, // final double trusted_strength, // trusted correlation strength
clt_parameters.rig.pf_strength_rfloor, // final double strength_rfloor, // strength floor - relative to trusted clt_parameters.rig.pf_strength_rfloor, // final double strength_rfloor, // strength floor - relative to trusted
...@@ -2454,7 +2456,7 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2454,7 +2456,7 @@ if (debugLevel > -100) return true; // temporarily !
int fourq_min = clt_parameters.rig.pf_fourq_min; int fourq_min = clt_parameters.rig.pf_fourq_min;
int fourq_gap = clt_parameters.rig.pf_fourq_gap; int fourq_gap = clt_parameters.rig.pf_fourq_gap;
boolean run_avg = false; //ltavg_en boolean run_avg = true; // false; //ltavg_en
int lt_radius = clt_parameters.rig.ltavg_radius; int lt_radius = clt_parameters.rig.ltavg_radius;
boolean strong_only = clt_parameters.rig.ltavg_dens_strong; boolean strong_only = clt_parameters.rig.ltavg_dens_strong;
int need_tiles = clt_parameters.rig.ltavg_dens_tiles; int need_tiles = clt_parameters.rig.ltavg_dens_tiles;
...@@ -2463,8 +2465,9 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2463,8 +2465,9 @@ if (debugLevel > -100) return true; // temporarily !
double min_disparity = clt_parameters.rig.ltavg_min_disparity; double min_disparity = clt_parameters.rig.ltavg_min_disparity;
double max_density = clt_parameters.rig.ltavg_max_density; double max_density = clt_parameters.rig.ltavg_max_density;
int grow = clt_parameters.rig.ltavg_grow; // each 2 add 8 directions step. Odd have last step in 4 ortho directions only. int gap_hwidth = clt_parameters.rig.ltavg_gap_hwidth;
int shrink = clt_parameters.rig.ltavg_shrink; // shrink after expanding. Combination of both fills small gaps int clust_hwidth = clt_parameters.rig.ltavg_clust_hwidth;
int extra_grow = clt_parameters.rig.ltavg_extra_grow;
// smoothing parameters // smoothing parameters
boolean smooth_strength = clt_parameters.rig.ltavg_smooth_strength; // provide tile strength when smoothing target disparity boolean smooth_strength = clt_parameters.rig.ltavg_smooth_strength; // provide tile strength when smoothing target disparity
double neib_pull = clt_parameters.rig.ltavg_neib_pull; // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s double neib_pull = clt_parameters.rig.ltavg_neib_pull; // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s
...@@ -2472,6 +2475,15 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2472,6 +2475,15 @@ if (debugLevel > -100) return true; // temporarily !
double min_change = clt_parameters.rig.ltavg_min_change; // double min_change = clt_parameters.rig.ltavg_min_change; //
int ref_smpl_radius = 11; // final int smpl_radius,
int ref_smpl_num = 50; // final int smpl_num_narrow, // = 3; // Number after removing worst (should be >1)
double ref_max_adiff = 0.15; // final double max_adiff, // Maximal absolute difference between the center tile and friends
double ref_max_rdiff = 0.04; // final double max_rdiff, // Maximal relative difference between the center tile and friends
double ref_smpl_arms = 0.1; // final double smpl_arms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
double ref_smpl_rrms = 0.01; // final double smpl_rrms, // = 0.005; // Maximal RMS/disparity in addition to smplRms
GenericJTabbedDialog gd = new GenericJTabbedDialog("Set CLT parameters",900,1100); GenericJTabbedDialog gd = new GenericJTabbedDialog("Set CLT parameters",900,1100);
gd.addTab("Genearl","Select bi-scan to show and process"); gd.addTab("Genearl","Select bi-scan to show and process");
...@@ -2543,18 +2555,41 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2543,18 +2555,41 @@ if (debugLevel > -100) return true; // temporarily !
gd.addNumericField("Maximal density to consider it to be low textured area", max_density, 4,6,"", gd.addNumericField("Maximal density to consider it to be low textured area", max_density, 4,6,"",
"Select areas with lower density"); "Select areas with lower density");
gd.addNumericField("Grow selection, each two units get expanion in 8 directions", grow, 0,3,"", gd.addNumericField("Maximal radius of a void in low-texture selection to fill" , gap_hwidth, 0,3,"",
"Two steps give one-tile expansion in 8 directions, odd numbers expand only in 4 ortho directions on the last expansion"); "Low textured selection may have gaps that will be filled");
gd.addNumericField("Shrink selection after growing", shrink, 0,3,"", gd.addNumericField("Minimal radius of a low-textured cluster to process", clust_hwidth, 0,3,"",
"Grow followed by shring fill small gaps"); "Remove low-textured areas smaller that twice this size in each orthogonal directions");
gd.addNumericField("Additionally grow low-textured areas selections", extra_grow, 0,3,"",
"Low textured areas will be grown by the radius of correlation averaging plus this value");
gd.addCheckbox ("Use tile strengths when filling gaps/smoothing", smooth_strength, gd.addCheckbox ("Use tile strengths when filling gaps/smoothing", smooth_strength,
"Unchecked - consider all tiles to have the same strength"); "Unchecked - consider all tiles to have the same strength");
gd.addNumericField("Relative pull of the nieghbor tiles compared to the original disparity" , neib_pull, 4,6,"", gd.addNumericField("Relative pull of the nieghbor tiles compared to the original disparity" , neib_pull, 4,6,"",
"If set to 0.0 - only gaps will be filled, defined disparities will not be modified"); "If set to 0.0 - only gaps will be filled, defined disparities will not be modified");
gd.addNumericField("Maximal number of smoothing / gap filling iterations to perform", max_iter, 0,3,"", gd.addNumericField("Maximal number of smoothing / gap filling iterations to perform", max_iter, 0,3,"",
"Safety limit for smoothing iterations "); "Safety limit for smoothing iterations ");
gd.addNumericField("Minimal disparity change to continue smoothing", min_change, 4,6,"pix",""); gd.addNumericField("Minimal disparity change to continue smoothing", min_change, 4,6,"pix","");
gd.addNumericField("How far to extend around a tile when refining averaging correlation measuremnts by planes ", ref_smpl_radius, 0,3,"tiles",
"Process a aquare centered at the current tile withthe side of twice this value plus 1 (2*pf_smpl_radius + 1)");
gd.addNumericField("Number after remaining in the sample square after removing worst fitting tiles", ref_smpl_num, 0,3,"",
"When fitting planes the outliers are removed until the number of remaining tiles equals this value");
gd.addNumericField("Maximal absolute disparity difference between the plane and tiles that fit", ref_max_adiff, 4,6,"pix",
"Maximal absolute disparity difference for fitting. Combined with the next one (relative) ");
gd.addNumericField("Maximal relative (to center disparity) difference between the plane and tiles that fit",ref_max_rdiff, 4,6,"pix/pix",
"This value is multipled by the tile disparity and added to the maximal absolute difference");
gd.addNumericField("Maximal absolute RMS of the remaining tiles in a sample", ref_smpl_arms, 4,6,"pix",
"After removing outliers RMS of the remaining tiles must be less than this value");
gd.addNumericField("Maximal relative (to center disparity) RMS of the remaining tiles in a sample", ref_smpl_rrms, 4,6,"pix/pix",
"Relative RMS times disparity is added to the absolute one");
// boolean run_avg = false; // boolean run_avg = false;
// int lt_radius = 1; // int lt_radius = 1;
...@@ -2604,13 +2639,22 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2604,13 +2639,22 @@ if (debugLevel > -100) return true; // temporarily !
min_disparity = gd.getNextNumber(); min_disparity = gd.getNextNumber();
max_density = gd.getNextNumber(); max_density = gd.getNextNumber();
grow= (int) gd.getNextNumber(); gap_hwidth= (int) gd.getNextNumber();
shrink= (int) gd.getNextNumber(); clust_hwidth= (int) gd.getNextNumber();
extra_grow= (int) gd.getNextNumber();
smooth_strength = gd.getNextBoolean(); smooth_strength = gd.getNextBoolean();
neib_pull = gd.getNextNumber(); neib_pull = gd.getNextNumber();
max_iter= (int) gd.getNextNumber(); max_iter= (int) gd.getNextNumber();
min_change = gd.getNextNumber(); min_change = gd.getNextNumber();
ref_smpl_radius= (int) gd.getNextNumber();
ref_smpl_num= (int) gd.getNextNumber();
ref_max_adiff= gd.getNextNumber();
ref_max_rdiff= gd.getNextNumber();
ref_smpl_arms= gd.getNextNumber();
ref_smpl_rrms= gd.getNextNumber();
System.out.println(" === showBiScan( parameters : ====="); System.out.println(" === showBiScan( parameters : =====");
System.out.println(" scan_index= "+scan_index); System.out.println(" scan_index= "+scan_index);
System.out.println(" show_smooth= "+show_smooth); System.out.println(" show_smooth= "+show_smooth);
...@@ -2652,13 +2696,22 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2652,13 +2696,22 @@ if (debugLevel > -100) return true; // temporarily !
System.out.println(" min_disparity= "+min_disparity); System.out.println(" min_disparity= "+min_disparity);
System.out.println(" max_density= "+max_density); System.out.println(" max_density= "+max_density);
System.out.println(" grow= "+grow); System.out.println(" gap_hwidth= "+gap_hwidth);
System.out.println(" shrink= "+shrink); System.out.println(" extra_grow= "+extra_grow);
System.out.println(" clust_hwidth= "+clust_hwidth);
System.out.println(" smooth_strength= "+smooth_strength); System.out.println(" smooth_strength= "+smooth_strength);
System.out.println(" neib_pull= "+neib_pull); System.out.println(" neib_pull= "+neib_pull);
System.out.println(" max_iter= "+max_iter); System.out.println(" max_iter= "+max_iter);
System.out.println(" min_change= "+min_change); System.out.println(" min_change= "+min_change);
System.out.println(" ref_smpl_radius= "+ref_smpl_radius);
System.out.println(" ref_smpl_num= "+ref_smpl_num);
System.out.println(" ref_max_adiff= "+ref_max_adiff);
System.out.println(" ref_max_rdiff= "+ref_max_rdiff);
System.out.println(" ref_smpl_arms= "+ref_smpl_arms);
System.out.println(" ref_smpl_rrms= "+ref_smpl_rrms);
BiScan biScan = biCamDSI_persistent.biScans.get(scan_index); BiScan biScan = biCamDSI_persistent.biScans.get(scan_index);
double [][] ds = null; double [][] ds = null;
if (show_smooth) { if (show_smooth) {
...@@ -2701,7 +2754,28 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2701,7 +2754,28 @@ if (debugLevel > -100) return true; // temporarily !
clt_parameters.tileY, // final int dbg_y, clt_parameters.tileY, // final int dbg_y,
debugLevel); // final int debugLevel); debugLevel); // final int debugLevel);
double [] density = biScan.getDensity(
strong_only, // final boolean strong_only,
need_tiles, // 20, // 10, // final int need_tiles,
max_radius, // 20, // 15, // final int max_radius,
clt_parameters.tileX, // final int dbg_x,
clt_parameters.tileY, // final int dbg_y,
debugLevel+2); // final int debugLevel
boolean [] pre_select = biScan.selectLowTextures(
min_disparity, // double min_disparity,
max_density, // double max_density,
lt_radius+extra_grow, // int grow,
gap_hwidth, // int max_gap_radius,
clust_hwidth, // int min_clust_radius,
density, // double [] density,
null); // double [] src_disparity);
double [] dbg_presel = new double [pre_select.length];
for (int i = 0; i < pre_select.length; i++) dbg_presel[i] = pre_select[i]? 1.0:0.0;
double [][] dbg_dens_str = {density, dbg_presel};
biScan.showScan(quadCLT_main.image_name+"-density-"+scan_index,dbg_dens_str);
ds = biScan.getFilteredDisparityStrength( ds = biScan.getFilteredDisparityStrength(
pre_select, // final boolean [] area_of_interest,
null, // final double [][] disparityStrength, null, // final double [][] disparityStrength,
min_disparity, // final double min_disparity, // keep original disparity far tiles min_disparity, // final double min_disparity, // keep original disparity far tiles
trusted_strength, // final double trusted_strength, // trusted correlation strength trusted_strength, // final double trusted_strength, // trusted correlation strength
...@@ -2734,23 +2808,15 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2734,23 +2808,15 @@ if (debugLevel > -100) return true; // temporarily !
clt_parameters.tileY, // final int dbg_y, clt_parameters.tileY, // final int dbg_y,
debugLevel+2); // final int debugLevel debugLevel+2); // final int debugLevel
biScan.showScan(quadCLT_main.image_name+"-BiScan-"+scan_index,ds); biScan.showScan(quadCLT_main.image_name+"-BiScan-"+scan_index,ds);
double [] density = biScan.getDensity(
strong_only, // final boolean strong_only,
need_tiles, // 20, // 10, // final int need_tiles,
max_radius, // 20, // 15, // final int max_radius,
clt_parameters.tileX, // final int dbg_x,
clt_parameters.tileY, // final int dbg_y,
debugLevel+2); // final int debugLevel
double [][] dbg_dens_str = {density, ds[1]};
biScan.showScan(quadCLT_main.image_name+"-density-"+scan_index,dbg_dens_str);
boolean [] lt_select = biScan.selectLowTextures( boolean [] lt_select = biScan.selectLowTextures(
min_disparity, // double min_disparity, min_disparity, // double min_disparity,
max_density, // double max_density, max_density, // double max_density,
grow, // int grow, lt_radius+extra_grow, // int grow,
shrink, // int shrink, gap_hwidth, // int max_gap_radius,
density, // double [] density, clust_hwidth, // int min_clust_radius,
ds[0]); // double [] src_disparity); density, // double [] density,
ds[0]); // double [] src_disparity);
double [][] ds1 = {ds[0].clone(), ds[1].clone()} ; double [][] ds1 = {ds[0].clone(), ds[1].clone()} ;
for (int i = 0; i < lt_select.length; i++) if (!lt_select[i]) { for (int i = 0; i < lt_select.length; i++) if (!lt_select[i]) {
ds1[0][i] = Double.NaN; ds1[0][i] = Double.NaN;
...@@ -2760,12 +2826,12 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2760,12 +2826,12 @@ if (debugLevel > -100) return true; // temporarily !
double [] lt_strength = smooth_strength? ds1[1]:null; double [] lt_strength = smooth_strength? ds1[1]:null;
double [][] ds2 = biScan.fillAndSmooth( double [][] ds2 = biScan.fillAndSmooth(
ds1[0], // final double [] src_disparity, ds1[0], // final double [] src_disparity,
lt_strength, // final double [] src_strength, // if not null will be used for weighted pull lt_strength, // final double [] src_strength, // if not null will be used for weighted pull
lt_select, // final boolean [] selection, lt_select, // final boolean [] selection,
neib_pull, // final double neib_pull, // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s neib_pull, // final double neib_pull, // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s
max_iter, // final int max_iterations, max_iter, // final int max_iterations,
min_change, // final double min_change, min_change, // final double min_change,
clt_parameters.tileX, // final int dbg_x, clt_parameters.tileX, // final int dbg_x,
clt_parameters.tileY, // final int dbg_y, clt_parameters.tileY, // final int dbg_y,
debugLevel+2); // final int debugLevel debugLevel+2); // final int debugLevel
...@@ -2810,8 +2876,59 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2810,8 +2876,59 @@ if (debugLevel > -100) return true; // temporarily !
final int refine_inter = 2; // 3; // 3 - dx, 2 - disparity final int refine_inter = 2; // 3; // 3 - dx, 2 - disparity
double [] scale_bad = new double [ds2[0].length]; double [] scale_bad = new double [ds2[0].length];
for (int i = 0; i < scale_bad.length; i++) scale_bad[i] = 1.0; for (int i = 0; i < scale_bad.length; i++) scale_bad[i] = 1.0;
// for (int nref = 0; nref < 5; nref++) { // clt_parameters.rig.num_inf_refine; nref++) { for (int nref = 0; nref < 7; nref++) { // clt_parameters.rig.num_inf_refine; nref++) {
for (int nref = 0; nref < clt_parameters.rig.num_inf_refine; nref++) { // for (int nref = 0; nref < clt_parameters.rig.num_inf_refine; nref++) {
double [][] disparity_bimap_new = refineRigAvg(
quadCLT_main, // QuadCLT quadCLT_main, // tiles should be set
quadCLT_aux, // QuadCLT quadCLT_aux,
disparity_bimap, // double [][] src_bimap, // current state of measurements (or null for new measurement)
prev_bimap, // double [][] prev_bimap, // previous state of measurements or null
scale_bad, // double [] scale_bad,
lt_select, // final boolean [] area_of_interest,
num_new, // int [] num_new,
clt_parameters, // EyesisCorrectionParameters.CLTParameters clt_parameters,
lt_radius, // final int lt_radius, // low texture mode - inter-correlation is averaged between the neighbors before argmax-ing, using (2*notch_mode+1)^2 square
biScan, // final BiScan biScan,
min_disparity, // final double min_disparity, // keep original disparity far tiles
trusted_strength, // final double trusted_strength, // trusted correlation strength
strength_rfloor,// final double strength_rfloor, // strength floor - relative to trusted
strength_pow, //final double strength_pow, // raise strength-floor to this power
ref_smpl_radius, // final int smpl_radius,
smpl_fract, // final double smpl_fract, // Number of friends among all neighbors
ref_smpl_num, // final int ref_smpl_num, // = 3; // Number after removing worst (should be >1)
ref_max_adiff, // final double max_adiff, // Maximal absolute difference betweenthe center tile and friends
ref_max_rdiff, // final double max_rdiff, // Maximal relative difference between the center tile and friends
max_atilt, // final double max_atilt, // = 2.0; // pix per tile
max_rtilt, // final double max_rtilt, // = 0.2; // (pix / disparity) per tile
ref_smpl_arms, // final double smpl_arms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
ref_smpl_rrms, // final double smpl_rrms, // = 0.005; // Maximal RMS/disparity in addition to smplRms
damp_tilt, // final double damp_tilt, // = 0.001; // Tilt cost for damping insufficient plane data
rwsigma, // final double rwsigma, // = 0.7; // influence of far neighbors diminish as a Gaussian with this sigma
goal_fraction_rms, //final double goal_fraction_rms, // Try to make rms to be this fraction of maximal acceptable by removing outliers
max_iter, // final int max_iterations,
min_change, // final double min_change,
clt_parameters.tileX, // final int dbg_x,
clt_parameters.tileY, // final int dbg_y,
threadsMax, // final int threadsMax, // maximal number of threads to launch
updateStatus, // final boolean updateStatus,
debugLevel); // final int debugLevel);
prev_bimap = disparity_bimap;
disparity_bimap = disparity_bimap_new;
if (debugLevel > -10) {(new showDoubleFloatArrays()).showArrays(
disparity_bimap,
tilesX,
disparity_bimap[0].length/tilesX,
true,
quadCLT_main.image_name+"RE-MEASURED_R"+lt_radius+"-N"+nref,
ImageDtt.BIDISPARITY_TITLES);
}
/*
// refine infinity using inter correlation // refine infinity using inter correlation
double [][] disparity_bimap_new = refineRigSel( double [][] disparity_bimap_new = refineRigSel(
quadCLT_main, // QuadCLT quadCLT_main, // tiles should be set quadCLT_main, // QuadCLT quadCLT_main, // tiles should be set
...@@ -2836,7 +2953,7 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2836,7 +2953,7 @@ if (debugLevel > -100) return true; // temporarily !
prev_bimap = disparity_bimap; prev_bimap = disparity_bimap;
disparity_bimap = disparity_bimap_new; disparity_bimap = disparity_bimap_new;
// re-smooth target disparity // re-smooth target disparity
if (debugLevel > 10) {(new showDoubleFloatArrays()).showArrays( if (debugLevel > -10) {(new showDoubleFloatArrays()).showArrays(
disparity_bimap, disparity_bimap,
tilesX, tilesX,
disparity_bimap[0].length/tilesX, disparity_bimap[0].length/tilesX,
...@@ -2844,31 +2961,74 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2844,31 +2961,74 @@ if (debugLevel > -100) return true; // temporarily !
quadCLT_main.image_name+"RE-MEASURED,R"+lt_radius, quadCLT_main.image_name+"RE-MEASURED,R"+lt_radius,
ImageDtt.BIDISPARITY_TITLES); ImageDtt.BIDISPARITY_TITLES);
} }
double [][] ds3 = biScan.fillAndSmooth( double [][] ds30 = {
disparity_bimap[ImageDtt.BI_TARGET_INDEX], // ds1[0], // final double [] src_disparity, disparity_bimap[ImageDtt.BI_TARGET_INDEX],
disparity_bimap[ImageDtt.BI_STR_CROSS_INDEX]};
double [][] ds3 = biScan.getFilteredDisparityStrength(
lt_select, // final boolean [] area_of_interest,
ds30, // final double [][] disparityStrength,
min_disparity, // final double min_disparity, // keep original disparity far tiles
trusted_strength, // final double trusted_strength, // trusted correlation strength
0.5 * strength_rfloor,// final double strength_rfloor, // strength floor - relative to trusted
true, // final boolean discard_unreliable,// replace v
true, // final boolean discard_weak, // consider weak trusted tiles (not promoted to trusted) as empty
true, // final boolean discard_strong, // suggest new disparities even for strong tiles
strength_pow, // final double strength_pow, // raise strength-floor to this power
null, // final double [] smpl_radius_array, // space-variant radius
ref_smpl_radius, // final int smpl_radius,
0, // final int smpl_num, // = 3; // Number after removing worst (should be >1)
smpl_fract, // final double smpl_fract, // Number of friends among all neighbors
ref_smpl_num, // final int smpl_num_narrow, // = 3; // Number after removing worst (should be >1)
ref_max_adiff, // final double max_adiff, // Maximal absolute difference between the center tile and friends
ref_max_rdiff, // final double max_rdiff, // Maximal relative difference between the center tile and friends
max_atilt, // final double max_atilt, // = 2.0; // pix per tile
max_rtilt, // final double max_rtilt, // = 0.2; // (pix / disparity) per tile
ref_smpl_arms, // final double smpl_arms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
ref_smpl_rrms, // final double smpl_rrms, // = 0.005; // Maximal RMS/disparity in addition to smplRms
damp_tilt, // final double damp_tilt, // = 0.001; // Tilt cost for damping insufficient plane data
0.0, // final double rwsigma, // = 0.7; // influence of far neighbors diminish as a Gaussian with this sigma
rwsigma, // final double rwsigma_narrow, // = used to determine initial tilt
1.0, // final double center_weight, // use center tile too (0.0 - do not use)
false, // final boolean use_alt, // use tiles from other scans if they fit better
goal_fraction_rms, // final double goal_fraction_rms, // Try to make rms to be this fraction of maximal acceptable by removing outliers
0.8, // boost_low_density, //final double boost_low_density, // 0 - strength is proportional to 1/density, 1.0 - same as remaining tiles
0, // final int fourq_min, // each of the 4 corners should have at least this number of tiles.
0, // final int fourq_gap, // symmetrical vertical and horizontal center areas that do not belong to any corner
clt_parameters.tileX, // final int dbg_x,
clt_parameters.tileY, // final int dbg_y,
debugLevel+2); // final int debugLevel
biScan.showScan(quadCLT_main.image_name+"-BiScan-"+scan_index+"-"+nref,ds3);
double [][] ds4 = biScan.fillAndSmooth(
ds3[0], // disparity_bimap[ImageDtt.BI_TARGET_INDEX], // ds1[0], // final double [] src_disparity,
null, // lt_strength, // final double [] src_strength, // if not null will be used for weighted pull null, // lt_strength, // final double [] src_strength, // if not null will be used for weighted pull
lt_select, // final boolean [] selection, lt_select, // final boolean [] selection,
neib_pull, // final double neib_pull, // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s 0.0, // only gaps neib_pull, // final double neib_pull, // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s
max_iter, // final int max_iterations, max_iter, // final int max_iterations,
min_change, // final double min_change, min_change, // final double min_change,
clt_parameters.tileX, // final int dbg_x, clt_parameters.tileX, // final int dbg_x,
clt_parameters.tileY, // final int dbg_y, clt_parameters.tileY, // final int dbg_y,
debugLevel+2); // final int debugLevel debugLevel+2); // final int debugLevel
if (debugLevel > 10) {
biScan.showScan(quadCLT_main.image_name+"-resmooth-"+nref,ds3); // Set disparity_bimap[ImageDtt.BI_TARGET_INDEX]from processed disparity
disparity_bimap[ImageDtt.BI_TARGET_INDEX] = ds4[0];
if (debugLevel > -10) {
biScan.showScan(quadCLT_main.image_name+"-resmooth-"+nref,ds4);
} }
/*
trusted_measurements = getTrustedDisparityInter(
0.0, // clt_parameters.rig.lt_trusted_strength*clt_parameters.rig.lt_need_friends, // double min_inter_strength, // check correlation strength combined for all 3 correlations
clt_parameters.grow_disp_trust, // double max_trusted_disparity,
trusted_measurements, // boolean [] was_trusted,
disparity_bimap ); // double [][] bimap // current state of measurements
*/ */
if (debugLevel > -2) { if (debugLevel > -2) {
System.out.println("groundTruthByRigPlanes(): refinement step="+nref+" num_new= "+num_new[0]+" tiles"); System.out.println("groundTruthByRigPlanes(): refinement step="+nref+" num_new= "+num_new[0]+" tiles");
} }
if (num_new[0] < clt_parameters.rig.pf_min_new) break; if (num_new[0] < clt_parameters.rig.pf_min_new) break;
} }
(new showDoubleFloatArrays()).showArrays( (new showDoubleFloatArrays()).showArrays(
...@@ -2878,7 +3038,6 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2878,7 +3038,6 @@ if (debugLevel > -100) return true; // temporarily !
true, true,
quadCLT_main.image_name+"CORR-AVG"+lt_radius, quadCLT_main.image_name+"CORR-AVG"+lt_radius,
ImageDtt.BIDISPARITY_TITLES); ImageDtt.BIDISPARITY_TITLES);
} }
...@@ -2889,6 +3048,183 @@ if (debugLevel > -100) return true; // temporarily ! ...@@ -2889,6 +3048,183 @@ if (debugLevel > -100) return true; // temporarily !
return true; return true;
} }
public double [][] refineRigAvg(
QuadCLT quadCLT_main, // tiles should be set
QuadCLT quadCLT_aux,
double [][] src_bimap, // current state of measurements
double [][] prev_bimap, // previous state of measurements or null
double [] scale_bad,
final boolean [] area_of_interest,
int [] num_new,
EyesisCorrectionParameters.CLTParameters clt_parameters,
final int lt_radius, // low texture mode - inter-correlation is averaged between the neighbors before argmax-ing, using (2*notch_mode+1)^2 square
final BiScan biScan,
// final double [][] disparityStrength,
final double min_disparity, // keep original disparity far tiles
final double trusted_strength, // trusted correlation strength
final double strength_rfloor, // strength floor - relative to trusted
final double strength_pow, // raise strength-floor to this power
final int smpl_radius,
final double smpl_fract, // Number of friends among all neighbors
final int ref_smpl_num, // = 3; // Number after removing worst (should be >1)
final double max_adiff, // Maximal absolute difference betweenthe center tile and friends
final double max_rdiff, // Maximal relative difference between the center tile and friends
final double max_atilt, // = 2.0; // pix per tile
final double max_rtilt, // = 0.2; // (pix / disparity) per tile
final double smpl_arms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
final double smpl_rrms, // = 0.005; // Maximal RMS/disparity in addition to smplRms
final double damp_tilt, // = 0.001; // Tilt cost for damping insufficient plane data
final double rwsigma, // = 0.7; // influence of far neighbors diminish as a Gaussian with this sigma
final double goal_fraction_rms, // Try to make rms to be this fraction of maximal acceptable by removing outliers
final int max_iterations,
final double min_change,
final int dbg_x,
final int dbg_y,
final int threadsMax, // maximal number of threads to launch
final boolean updateStatus,
final int debugLevel)
{
int tilesX =quadCLT_main.tp.getTilesX();
int tilesY =quadCLT_main.tp.getTilesY();
int [][] tile_op = new int [tilesY][tilesX];
double [][] disparity_array = new double [tilesY][tilesX];
double disp_scale_main = 1.0/clt_parameters.corr_magic_scale; // Is it needed?
double disp_scale_aux = disp_scale_main * quadCLT_main.geometryCorrection.getDisparityRadius()/quadCLT_aux.geometryCorrection.getDisparityRadius();
double disp_scale_inter = disp_scale_main * quadCLT_main.geometryCorrection.getDisparityRadius()/quadCLT_aux.geometryCorrection.getBaseline();
int tile_op_all = clt_parameters.tile_task_op; //FIXME Use some constant?
int numMeas = 0;
double [][] ds_ref = new double[2][];
ds_ref[0] = new double [tilesX*tilesY];
for (int tileY = 0; tileY<tilesY;tileY++) {
for (int tileX = 0; tileX<tilesX;tileX++) {
int nTile = tileY * tilesX + tileX;
if (((area_of_interest == null) || area_of_interest[nTile]) && !Double.isNaN(src_bimap[ImageDtt.BI_TARGET_INDEX][nTile])) {
if (prepRefineTile(
(lt_radius > 0),
clt_parameters, // EyesisCorrectionParameters.CLTParameters clt_parameters,
tile_op_all, // int tile_op_all,
src_bimap, // double [][] src_bimap, // current state of measurements
prev_bimap, // double [][] prev_bimap, // previous state of measurements or null
scale_bad, // double [] scale_bad,
tile_op, // int [][] tile_op, // common for both amin and aux
disparity_array, // double [][] disparity_array,
2, // int refine_mode, // 0 - by main, 1 - by aux, 2 - by inter
false, // boolean keep_inf, // keep expected disparity 0.0 if it was so
0.0, // double refine_min_strength, // do not refine weaker tiles
0.0, // double refine_tolerance, // do not refine if absolute disparity below
disp_scale_main, // double disp_scale_main, // 1.0
disp_scale_aux, //double disp_scale_aux, // ~0.58
disp_scale_inter, //double disp_scale_inter, // ~4.86
// scale_step, // double scale_step, // scale for "unstable tiles"
tileX, // int tileX,
tileY, // int tileY,
nTile )) {
numMeas++; //int nTile
ds_ref[0][nTile] = disparity_array[tileY][tileX];
}
}
}
}
ds_ref[1] = src_bimap[ImageDtt.BI_STR_CROSS_INDEX];
if (debugLevel > -2) {
System.out.println("refineRigAvg(): prepared "+numMeas+" to measure");
}
double [][] ds_planes = biScan.getFilteredDisparityStrength(
area_of_interest, // final boolean [] area_of_interest,
ds_ref, // final double [][] disparityStrength,
min_disparity, // final double min_disparity, // keep original disparity far tiles
trusted_strength, // final double trusted_strength, // trusted correlation strength
0.5 * strength_rfloor,// final double strength_rfloor, // strength floor - relative to trusted
true, // final boolean discard_unreliable,// replace v
true, // final boolean discard_weak, // consider weak trusted tiles (not promoted to trusted) as empty
true, // final boolean discard_strong, // suggest new disparities even for strong tiles
strength_pow, // final double strength_pow, // raise strength-floor to this power
null, // final double [] smpl_radius_array, // space-variant radius
smpl_radius, // final int smpl_radius,
0, // final int smpl_num, // = 3; // Number after removing worst (should be >1)
smpl_fract, // final double smpl_fract, // Number of friends among all neighbors
ref_smpl_num, // final int smpl_num_narrow, // = 3; // Number after removing worst (should be >1)
max_adiff, // final double max_adiff, // Maximal absolute difference between the center tile and friends
max_rdiff, // final double max_rdiff, // Maximal relative difference between the center tile and friends
max_atilt, // final double max_atilt, // = 2.0; // pix per tile
max_rtilt, // final double max_rtilt, // = 0.2; // (pix / disparity) per tile
smpl_arms, // final double smpl_arms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
smpl_rrms, // final double smpl_rrms, // = 0.005; // Maximal RMS/disparity in addition to smplRms
damp_tilt, // final double damp_tilt, // = 0.001; // Tilt cost for damping insufficient plane data
0.0, // final double rwsigma, // = 0.7; // influence of far neighbors diminish as a Gaussian with this sigma
rwsigma, // final double rwsigma_narrow, // = used to determine initial tilt
1.0, // final double center_weight, // use center tile too (0.0 - do not use)
false, // final boolean use_alt, // use tiles from other scans if they fit better
goal_fraction_rms, // final double goal_fraction_rms, // Try to make rms to be this fraction of maximal acceptable by removing outliers
0.8, // boost_low_density, //final double boost_low_density, // 0 - strength is proportional to 1/density, 1.0 - same as remaining tiles
0, // final int fourq_min, // each of the 4 corners should have at least this number of tiles.
0, // final int fourq_gap, // symmetrical vertical and horizontal center areas that do not belong to any corner
clt_parameters.tileX, // final int dbg_x,
clt_parameters.tileY, // final int dbg_y,
debugLevel+2); // final int debugLevel
// fill NaN gaps:
double [][] ds_no_gaps = biScan.fillAndSmooth(
ds_planes[0], // disparity_bimap[ImageDtt.BI_TARGET_INDEX], // ds1[0], // final double [] src_disparity,
null, // lt_strength, // final double [] src_strength, // if not null will be used for weighted pull
area_of_interest, // final boolean [] selection,
0.0, // only gaps neib_pull, // final double neib_pull, // pull to weighted average relative to pull to the original disparity value. If 0.0 - will only update former NaN-s
max_iterations, // final int max_iterations,
min_change, // final double min_change,
clt_parameters.tileX, // final int dbg_x,
clt_parameters.tileY, // final int dbg_y,
debugLevel+2); // final int debugLevel
// reformat back to disparity_array
for (int tileY = 0; tileY<tilesY;tileY++) {
for (int tileX = 0; tileX<tilesX;tileX++) {
int nTile = tileY * tilesX + tileX;
disparity_array[tileY][tileX] = ds_no_gaps[0][nTile];
}
}
double [][] disparity_bimap = measureRig(
quadCLT_main, // QuadCLT quadCLT_main, // tiles should be set
quadCLT_aux, // QuadCLT quadCLT_aux,
tile_op, // int [][] tile_op, // common for both amin and aux
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,
false, // final boolean notch_mode, // use notch filter for inter-camera correlation to detect poles
lt_radius, // final int // low texture mode - inter-correlation is averaged between the neighbors before argmax-ing, using
true, // final boolean no_int_x0, // do not offset window to integer maximum - used when averaging low textures to avoid "jumps" for very wide
threadsMax, //final int threadsMax, // maximal number of threads to launch
updateStatus, // final boolean updateStatus,
debugLevel); // final int debugLevel)
// combine with old results for tiles that were not re-measured
// not needed here as so far everything selected is re-measured in the averaging mode)
/*
for (int tileY = 0; tileY<tilesY;tileY++) {
for (int tileX = 0; tileX<tilesX;tileX++) {
int nTile = tileY * tilesX + tileX;
if ((selection == null) || selection[nTile]) {
if (Double.isNaN(disparity_bimap[ImageDtt.BI_TARGET_INDEX][nTile]) && !Double.isNaN(src_bimap[ImageDtt.BI_TARGET_INDEX][nTile])) {
for (int i = 0; i < disparity_bimap.length; i++) {
disparity_bimap[i][nTile] = src_bimap[i][nTile];
}
}
}
}
}
*/
if (num_new != null) {
num_new[0] = numMeas;
}
return disparity_bimap;
}
public double [][] groundTruthByRig( public double [][] groundTruthByRig(
QuadCLT quadCLT_main, // tiles should be set QuadCLT quadCLT_main, // tiles should be set
......
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