Commit f580e71e authored by Andrey Filippov's avatar Andrey Filippov

tested new fiel calibration with ers

parent b47dba20
...@@ -85,7 +85,7 @@ import ij.process.ImageProcessor; ...@@ -85,7 +85,7 @@ import ij.process.ImageProcessor;
} }
} }
ImagePlus imp_stack = new ImagePlus(title, array_stack); ImagePlus imp_stack = new ImagePlus(title, array_stack); // stack is empty
imp_stack.getProcessor().resetMinAndMax(); imp_stack.getProcessor().resetMinAndMax();
imp_stack.show(); imp_stack.show();
return; return;
......
...@@ -34,7 +34,12 @@ public class CLTPass3d{ ...@@ -34,7 +34,12 @@ public class CLTPass3d{
private double [][] disparity_sav; // saved disparity private double [][] disparity_sav; // saved disparity
private int [][] tile_op_sav; // saved tile_op private int [][] tile_op_sav; // saved tile_op
public double [][] disparity_map = null; // add 4 layers - worst difference for the port public double [][] disparity_map = null; // add 4 layers - worst difference for the port
public double [][] lazy_eye_data = null;
public int lma_cluster_size = -1;
public boolean [] lazy_eye_force_disparity = null;
double [] calc_disparity = null; // composite disparity, calculated from "disparity", and "disparity_map" fields double [] calc_disparity = null; // composite disparity, calculated from "disparity", and "disparity_map" fields
// using horizontal features and corr_magic_scale // using horizontal features and corr_magic_scale
// used directly in TileProcessor.compositeScan() // used directly in TileProcessor.compositeScan()
double [] calc_disparity_hor = null; // composite disparity, calculated from "disparity", and "disparity_map" fields double [] calc_disparity_hor = null; // composite disparity, calculated from "disparity", and "disparity_map" fields
...@@ -235,6 +240,31 @@ public class CLTPass3d{ ...@@ -235,6 +240,31 @@ public class CLTPass3d{
} }
public boolean [] getLazyEyeForceDisparity() {
return lazy_eye_force_disparity;
}
public void setLazyEyeForceDisparity(boolean [] lazy_eye_force_disparity) {
this.lazy_eye_force_disparity = lazy_eye_force_disparity;
}
public double [][] getLazyEyeData() {
return lazy_eye_data;
}
public void setLazyEyeData(double [][] lazy_eye_data) {
this.lazy_eye_data = lazy_eye_data;
}
public int getLazyEyeClusterSize() {
return lma_cluster_size;
}
public void setLazyEyeClusterSize(int lma_cluster_size) {
this.lma_cluster_size = lma_cluster_size;
}
public boolean [] getSelected(){ public boolean [] getSelected(){
return selected; return selected;
} }
......
...@@ -1948,13 +1948,13 @@ public class Correlation2d { ...@@ -1948,13 +1948,13 @@ public class Correlation2d {
} }
if (debug_graphic) { if (debug_graphic && (dbg_corr != null)) {
double [][] dbg_corrs = repackCluster( double [][] dbg_corrs = repackCluster(
dbg_corr, dbg_corr,
clust_width); clust_width);
(new ShowDoubleFloatArrays()).showArrays( (new ShowDoubleFloatArrays()).showArrays( // empty array
dbg_corrs, dbg_corrs,
dbg_out_width, dbg_out_width,
dbg_out_height, dbg_out_height,
......
...@@ -99,7 +99,7 @@ public class ImageDttParameters { ...@@ -99,7 +99,7 @@ public class ImageDttParameters {
public double corr_wndx_blur = 5.0; // 100% to 0 % vertical transition range public double corr_wndx_blur = 5.0; // 100% to 0 % vertical transition range
// LMA parameters // LMA parameters
public double lma_disp_range = 2.0; // disparity range to combine in one cluster (to mitigate ERS public double lma_disp_range = 5.0; // disparity range to combine in one cluster (to mitigate ERS
// LMA single parameters // LMA single parameters
public boolean lmas_gaussian = false; // model correlation maximum as a Gaussian (false - as a parabola) public boolean lmas_gaussian = false; // model correlation maximum as a Gaussian (false - as a parabola)
public boolean lmas_adjust_wm = true; // used in new for width public boolean lmas_adjust_wm = true; // used in new for width
...@@ -110,16 +110,16 @@ public class ImageDttParameters { ...@@ -110,16 +110,16 @@ public class ImageDttParameters {
public double lmas_poly_str_min = 0.05; // ignore tiles with poly strength (scaled) below public double lmas_poly_str_min = 0.05; // ignore tiles with poly strength (scaled) below
public double lmas_lambda_initial = 0.03; // public double lmas_lambda_initial = 0.03; //
public double lmas_rms_diff = 0.001; // public double lmas_rms_diff = 0.0003; //
public int lmas_num_iter = 20; // public int lmas_num_iter = 20; //
// Filtering and strength calculation // Filtering and strength calculation
public double lmas_max_rel_rms = 0.2; // maximal relative (to average max/min amplitude LMA RMS) // May be up to 0.3) public double lmas_max_rel_rms = 0.3; // maximal relative (to average max/min amplitude LMA RMS) // May be up to 0.3)
public double lmas_min_strength = 1.0; // minimal composite strength (sqrt(average amp squared over absolute RMS) public double lmas_min_strength = 0.7; // minimal composite strength (sqrt(average amp squared over absolute RMS)
public double lmas_min_ac = 0.03; // minimal of a and C coefficients maximum (measures sharpest point/line) public double lmas_min_ac = 0.02; // minimal of a and C coefficients maximum (measures sharpest point/line)
public double lmas_max_area = 0.0; // maximal half-area (if > 0.0) public double lmas_max_area = 0.0; // maximal half-area (if > 0.0)
public boolean lma_gaussian = false; // model correlation maximum as a Gaussian (false - as a parabola) public boolean lma_gaussian = false; // model correlation maximum as a Gaussian (false - as a parabola)
public boolean lma_second = false; // re-run LMA after removing weak/failed tiles public boolean lma_second = true; // re-run LMA after removing weak/failed tiles
public boolean lma_second_gaussian = false; // re-run after removing weal/failed in Gaussian mode public boolean lma_second_gaussian = false; // re-run after removing weal/failed in Gaussian mode
public boolean lma_adjust_wm = true; // used in new for width public boolean lma_adjust_wm = true; // used in new for width
public boolean lma_adjust_wy = true; // false; // used in new for ellipse public boolean lma_adjust_wy = true; // false; // used in new for ellipse
...@@ -128,7 +128,7 @@ public class ImageDttParameters { ...@@ -128,7 +128,7 @@ public class ImageDttParameters {
public boolean lma_adjust_ag = true; // used in new for gains public boolean lma_adjust_ag = true; // used in new for gains
// new LMA parameters // new LMA parameters
public double lma_wnd = 1.5; // raise cosine window to this power (1.0 - just 2D cosine) public double lma_wnd = 1.0; //1.5; // raise cosine window to this power (1.0 - just 2D cosine)
public double lma_min_wnd = 0.4; // divide values by the 2D correlation window if it is >= this value for finding maximums and convex areas public double lma_min_wnd = 0.4; // divide values by the 2D correlation window if it is >= this value for finding maximums and convex areas
public double lma_wnd_pwr = 0.8; // Raise window for finding a maximum and a convex region to this power public double lma_wnd_pwr = 0.8; // Raise window for finding a maximum and a convex region to this power
public int lma_hard_marg = 1; // Zero out this width margins before blurring public int lma_hard_marg = 1; // Zero out this width margins before blurring
...@@ -148,13 +148,13 @@ public class ImageDttParameters { ...@@ -148,13 +148,13 @@ public class ImageDttParameters {
public double lma_lambda_scale_good = 0.5; // public double lma_lambda_scale_good = 0.5; //
public double lma_lambda_scale_bad = 8.0; // public double lma_lambda_scale_bad = 8.0; //
public double lma_lambda_max = 100.0; // public double lma_lambda_max = 100.0; //
public double lma_rms_diff = 0.001; // public double lma_rms_diff = 0.003; //
public int lma_num_iter = 20; // public int lma_num_iter = 10; //
// Filtering and strength calculation // Filtering and strength calculation
public double lma_max_rel_rms = 0.12; // maximal relative (to average max/min amplitude LMA RMS) // May be up to 0.3) public double lma_max_rel_rms = 0.2; // maximal relative (to average max/min amplitude LMA RMS) // May be up to 0.3)
public double lma_min_strength = 1.25; // minimal composite strength (sqrt(average amp squared over absolute RMS) public double lma_min_strength = 1.0; // minimal composite strength (sqrt(average amp squared over absolute RMS)
public double lma_min_ac = 0.15; // minimal of a and C coefficients maximum (measures sharpest point/line) public double lma_min_ac = 0.05; // minimal of a and C coefficients maximum (measures sharpest point/line)
public double lma_max_area = 30.0; // maximal half-area (if > 0.0) public double lma_max_area = 45.0; // maximal half-area (if > 0.0)
public double lma_str_scale = 0.2; // convert lma-generated strength to match previous ones - scale public double lma_str_scale = 0.2; // convert lma-generated strength to match previous ones - scale
public double lma_str_offset = 0.05; // convert lma-generated strength to match previous ones - add to result public double lma_str_offset = 0.05; // convert lma-generated strength to match previous ones - add to result
...@@ -162,8 +162,8 @@ public class ImageDttParameters { ...@@ -162,8 +162,8 @@ public class ImageDttParameters {
// Lazy eye results interpretation // Lazy eye results interpretation
public boolean lma_diff_xy = true; // convert dd/nd to x,y public boolean lma_diff_xy = true; // convert dd/nd to x,y
public double lma_diff_minw = 0.5; // minimal weight to keep public double lma_diff_minw = 0.07; // minimal weight to keep
public double lma_diff_sigma = 1.0; // blur differential data (relative to the cluster linear size) public double lma_diff_sigma = 2.0; // blur differential data (relative to the cluster linear size)
public int lma_debug_level = 0; // public int lma_debug_level = 0; //
public int lma_debug_level1 = 0; // public int lma_debug_level1 = 0; //
......
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