Working snapshot, before implementing CuasMotion.refineMotionVectors() (03a9cc77) · Commits · Elphel / imagej-elphel

src/main/java/com/elphel/imagej/cuas/CuasMotion.java

+149 −105

Original line number	Diff line number	Diff line
		@@ -1286,8 +1286,10 @@ public class CuasMotion {
		boolean skip_empty = true;
		int nseq0 = 0;
		int nseq1 = multi_targets.length -1;
		int tx = wh[0] / 2;
		int ty = wh[1] / 2;
		int tx0 = wh[0] / 2;
		int ty0 = wh[1] / 2;
		int twidth = 1;
		int theight = 1;
		int num_pars = CuasMotionLMA.RSLT_LEN; // pvf_top_titles[0].length; // .RSLT_LEN;
		int npar = CuasMotionLMA.RSLT_A;
		int fw = 9;
		@@ -1300,14 +1302,17 @@ public class CuasMotion {
		for (int i = 0; i < num_pars; i++) {
		choices[i + extra_choices.length] = String.format("%2d: %s", i, CuasMotionLMA.LMA_TITLES[i]); // pvf_top_titles[0])
		}

		while (true) {
		GenericJTabbedDialog gd1 = new GenericJTabbedDialog("Select Range",600,500);
		// gd1.addMessage(target_path);
		gd1.addNumericField("tile X (0.."+(wh[0] -1)+")", tx, 0, 3, "",
		gd1.addNumericField("tile X (0.."+(wh[0] -1)+")", tx0, 0, 3, "",
		"Select tile X");
		gd1.addNumericField("tile Y (0.."+(wh[1] -1)+")", ty, 0, 3, "",
		gd1.addNumericField("tile Y (0.."+(wh[1] -1)+")", ty0, 0, 3, "",
		"Select tile Y");
		gd1.addNumericField("tiles width (1.."+(wh[0])+")", twidth, 0, 3, "",
		"Select tiles rectangle width");
		gd1.addNumericField("tile height (1.."+(wh[1])+")", theight, 0, 3, "",
		"Select tile rectangle height");
		gd1.addNumericField("Start sequence (0.."+(multi_targets.length -1)+")", nseq0, 0, 3, "",
		"Select first scene to output");
		gd1.addNumericField("End sequence (0.."+(multi_targets.length -1)+")", nseq1, 0, 3, "",
		@@ -1328,8 +1333,10 @@ public class CuasMotion {
		gd1.showDialog();
		if (gd1.wasCanceled()) return;
		final int tileSize = GPUTileProcessor.DTT_SIZE; // 8
		tx = (int) gd1.getNextNumber();
		ty = (int) gd1.getNextNumber();
		tx0 = (int) gd1.getNextNumber();
		ty0 = (int) gd1.getNextNumber();
		twidth = (int) gd1.getNextNumber();
		theight = (int) gd1.getNextNumber();
		nseq0 = (int) gd1.getNextNumber();
		nseq1 = (int) gd1.getNextNumber();
		npar = gd1.getNextChoiceIndex() - extra_choices.length;
		@@ -1341,8 +1348,10 @@ public class CuasMotion {
		max_targets = (int) gd1.getNextNumber();


		tx = Math.max(Math.min(tx, wh[0] -1), 0);
		ty = Math.max(Math.min(ty, wh[1] -1), 0);
		tx0 = Math.max(Math.min(tx0, wh[0] -1), 0);
		ty0 = Math.max(Math.min(ty0, wh[1] -1), 0);
		twidth = Math.max(Math.min(twidth, wh[0] - tx0), 1);
		theight =Math.max(Math.min(theight, wh[1] - ty0), 1);
		nseq0 = Math.max(Math.min(nseq0, multi_targets.length -1), 0);
		nseq1 = Math.max(Math.min(nseq1, multi_targets.length -1), nseq0);
		npar = Math.max(Math.min(npar, num_pars -1), -extra_choices.length);
		@@ -1351,13 +1360,33 @@ public class CuasMotion {
		switch (mode) {
		case ANLZ_SECT:
		System.out.println("Displaying scenes from "+nseq0+" to "+nseq1+", parameter: "+choices[npar+extra_choices.length]); // CuasMotionLMA.LMA_TITLES
		System.out.println("tx="+tx+", ty="+ty);
		int ntile = tx + ty * wh[0];
		System.out.println("tx="+tx0+", ty="+ty0+", twidth="+twidth+", theight="+theight);
		// int ntile = tx0 + ty0 * wh[0];

		for (int nseq = nseq0; nseq <= nseq1; nseq++) {
		boolean has_targets = (multi_targets[nseq] != null) && (multi_targets[nseq][ntile] != null) && (multi_targets[nseq][ntile].length > 0);
		boolean [][] has_targ = new boolean [theight][twidth];
		boolean has_targets = false;
		for (int ty = ty0; ty < (ty0+theight); ty++) {
		for (int tx = tx0; tx < (tx0+twidth); tx++) {
		int ntile = tx + ty * wh[0];
		has_targ[ty-ty0][tx-tx0] = (multi_targets[nseq] != null) &&
		(multi_targets[nseq][ntile] != null) &&
		(multi_targets[nseq][ntile].length > 0);
		has_targets \|= has_targ[ty-ty0][tx-tx0];
		}
		}
		if (has_targets \|\| !skip_empty) {
		System.out.print(String.format("%17s, %4d, ",pvf_titles[0][nseq],nseq));
		if (has_targets) {
		for (int ty = ty0; ty < (ty0+theight); ty++) {
		for (int tx = tx0; tx < (tx0+twidth); tx++) {
		int ntile = tx + ty * wh[0];
		// boolean has_targets = (multi_targets[nseq] != null) && (multi_targets[nseq][ntile] != null) && (multi_targets[nseq][ntile].length > 0);
		if (has_targ[ty-ty0][tx-tx0] \|\| !skip_empty) {
		if ((theight * twidth) > 1) {
		System.out.print(String.format("%5s,%2d:%2d, ",ntile,tx,ty));
		}
		// System.out.print(String.format("%17s, %4d, ",pvf_titles[0][nseq],nseq));
		if (has_targ[ty-ty0][tx-tx0]) {
		int num_targ = multi_targets[nseq][ntile].length;
		for (int ntarg = 0; ntarg < num_targ; ntarg++) {
		switch (npar) {
		@@ -1391,8 +1420,12 @@ public class CuasMotion {
		default:
		System.out.print(String.format("%"+fw+"f",multi_targets[nseq][ntile][ntarg][npar]));
		}
		if (ntarg < (num_targ-1)) {
		// if (ntarg < (num_targ-1)) {
		System.out.print(", ");
		// }
		}
		}
		// System.out.println();
		}
		}
		}
		@@ -1406,7 +1439,8 @@ public class CuasMotion {
		case ANLZ_EQ: // list tiles with targets with parameter equal (such as FAILURE==0)
		case ANLZ_GE: // list tiles with targets with parameter >= value (such as AMPLITUDE >= 1.0)
		case ANLZ_LE: // list tiles with targets with parameter <= value (such as RMSE <= 0.5)
		System.out.print("\nLooking for tiles in each scene from "+nseq0+" to "+nseq1);
		System.out.print("\nLooking for tiles in each scene from "+nseq0+" to "+nseq1+
		", "+tx0+"<=tx<="+(tx0 + twidth-1)+", "+ty0+"<=ty<="+(ty0 + theight-1));
		switch (mode) {
		case ANLZ_NEMPTY: System.out.print(" that contain at least one target"); break;
		case ANLZ_DEFINED: System.out.print(" that contain at least one target with non-NaN "+choices[npar+extra_choices.length]+" value"); break;
		@@ -1427,7 +1461,9 @@ public class CuasMotion {
		}
		for (int nseq = nseq0; nseq <= nseq1; nseq++) {
		ArrayList<Integer> tiles_list = new ArrayList<Integer>();
		for (ntile = 0; ntile < num_tiles; ntile++){
		for (int ty = ty0; ty < (ty0+theight); ty++) {
		for (int tx = tx0; tx < (tx0+twidth); tx++) {
		int ntile = tx + ty * wh[0];
		boolean has_targets = (multi_targets[nseq] != null) &&
		(multi_targets[nseq][ntile] != null) &&
		(multi_targets[nseq][ntile].length > 0);
		@@ -1469,7 +1505,9 @@ public class CuasMotion {
		}
		}
		}
		}
		} // for (int tx = tx0; tx < (tx0+twidth); tx++) {
		} // for (int ty = ty0; ty < (ty0+theight); ty++) {

		if (!tiles_list.isEmpty() \|\| !skip_empty) {
		System.out.print(String.format("%17s, %4d, targets:%5d",pvf_titles[0][nseq],nseq, tiles_list.size()));
		if (!tiles_list.isEmpty()) {
		@@ -1485,7 +1523,7 @@ public class CuasMotion {
		}
		System.out.println();
		}
		}
		} // for (int nseq = nseq0; nseq <= nseq1; nseq++)
		break;
		} // switch (mode)
		}
		@@ -7250,17 +7288,14 @@ public class CuasMotion {
		int corr_pairs = clt_parameters.imp.cuas_corr_pairs; // 20 (50)

		double boost_pairs = slow_mode? 1.0: clt_parameters.imp.cuas_boost_slow; // 4.0; // if >1 and the motion vector is below tile_size/cuas_boost_slow, scale corr_pairs
		double boost_mv_lim = clt_parameters.imp.cuas_boost_mv_lim; // 0.2; // Do not boost if motion vector faster than this (before in code equiv 1.8 pix)
		double boost_mstr = clt_parameters.imp.cuas_boost_mstr; // 0.007; // scale corr_pairs if motion strength is below

		// int precorr_ra = clt_parameters.imp.cuas_precorr_ra; // 4 (10)
		double boost_xstr = clt_parameters.imp.cuas_boost_xstr; // 0.007; // scale corr_pairs if motion strength is below
		int corr_ra_step = clt_parameters.imp.cuas_corr_step; // 2 ( 2)
		double fat_zero = clt_parameters.imp.cuas_fat_zero;
		double cent_radius = clt_parameters.imp.cuas_cent_radius;
		int n_recenter = clt_parameters.imp.cuas_n_recenter;
		double rstr = clt_parameters.imp.cuas_rstr;// 0.003; // clt_parameters.imp.rln_sngl_rstr; // FIXME: ADD
		// double speed_min = clt_parameters.imp.cuas_speed_min;
		// double speed_pref = clt_parameters.imp.cuas_speed_pref;
		// double speed_boost = clt_parameters.imp.cuas_speed_boost;
		boolean smooth = clt_parameters.imp.cuas_smooth; // true;
		boolean half_step = clt_parameters.imp.cuas_half_step; // true;
		double [][] target_frac = new double [clt_parameters.imp.cuas_target_frac.length][2];
		@@ -7404,7 +7439,9 @@ public class CuasMotion {
		target_sequence, // final double [][][] target_sequence,
		target_sequence_boost, // final double [][][] target_boosted,
		boost_pairs, // final double boost_slow, // 4.0;
		boost_mv_lim, // final double boost_mv_lim, 1.5-1.8
		boost_mstr, // final double boost_mstr,
		boost_xstr, // final double boost_xstr, // 0.2
		debugLevel); // final int debugLevel)

		if (corr2d_save_show) { // may be read to re-process with vector field
		@@ -7495,20 +7532,24 @@ public class CuasMotion {
		* @param target_sequence target sequence with only motion vectors defined for specified number of correlation pairs
		* @param target_boosted same for increased number of correlation
		* @param boost_slow use boosted if motion vector is smaller than this
		* @param boost_mv_lim Do not boost if faster
		* @param boost_mstr use boosted if motion vector strength is smaller than this
		* @param boost_xstr never boost if stronger
		* @param debugLevel debug level
		*/
		public static void combineSlowBoosted(
		final double [][][] target_sequence,
		final double [][][] target_boosted,
		final double boost_slow, // 4.0;
		final double boost_mv_lim,
		final double boost_mstr,
		final double boost_xstr,
		final int debugLevel) {
		if (boost_slow >1) {
		final Thread[] threads = ImageDtt.newThreadArray();
		final AtomicInteger ai = new AtomicInteger(0);
		final double max_v = 0.9 * GPUTileProcessor.DTT_SIZE / boost_slow;
		final double max_v2 = max_v * max_v;
		// final double max_v = 0.9 * GPUTileProcessor.DTT_SIZE / boost_slow;
		final double max_v2 = boost_mv_lim * boost_mv_lim; // max_v * max_v;
		if (debugLevel > -4) {
		System.out.println("combineSlowBoosted(): boost_slow="+boost_slow+", boost_mstr="+boost_mstr+", max_v2="+max_v2);
		}
		@@ -7524,9 +7565,9 @@ public class CuasMotion {
		target[ntile] = target_b[ntile];
		} else {
		boolean replace = false;
		if (!(target[ntile][CuasMotionLMA.RSLT_VSTR] >= boost_mstr)) {
		if (!(target[ntile][CuasMotionLMA.RSLT_VSTR] >= boost_mstr)) { // boost all weak MV
		replace = true;
		} else {
		} else if (!(target[ntile][CuasMotionLMA.RSLT_VSTR] > boost_xstr)){ // do not boost strong MV
		double vx = target[ntile][CuasMotionLMA.RSLT_VX];
		double vy = target[ntile][CuasMotionLMA.RSLT_VY];
		double vv = vxvx+vyvy;
		@@ -8201,6 +8242,9 @@ public class CuasMotion {
		// Calculate both centroid and LMA target parametes, return both
		// targets_new will contain motion vectors, centroid, and LMA results combined
		//save_filtered_high



		float [][] accum_debug = save_filtered_high? new float [num_corr_samples][]:null; //fpixels_accumulated.length]
		boolean keep_failed = false; // keep failed targets
		double [][][][] targets_new_multi = getAccumulatedCoordinatesMulti(

src/main/java/com/elphel/imagej/tileprocessor/IntersceneMatchParameters.java

+55 −3

Original line number	Diff line number	Diff line
		@@ -794,8 +794,10 @@ min_str_neib_fpn 0.35
		public boolean cuas_smooth = true; // used cosine window when averaging correlations
		public int cuas_corr_pairs = 20; // number of correlation pairs to accumulate
		public double cuas_boost_slow = 4.0; // if >1 and the motion vector is below tile_size/cuas_boost_slow, scale corr_pairs
		public double cuas_boost_mv_lim = 1.8; // Do not boost if motion vector faster than this (before in code equiv 1.8 pix)
		public double cuas_boost_accum = 4.0; // if >1 increase tracking camera exposure (TODO: conditional / compete)
		public double cuas_boost_mstr = 0.007; // scale corr_pairs if motion strength is below
		public double cuas_boost_xstr = 0.2; // never scale if stronger
		public int cuas_corr_offset = 5; // offset between motion detection pairs
		public boolean cuas_gaussian_ra = true; // use gaussian temporal Gaussian instead of running average
		public int cuas_temporal_um = 100; // temporal "unsharp mask" - subtract running
		@@ -808,6 +810,13 @@ min_str_neib_fpn 0.35
		public int cuas_max_range = 2; // how far to extend local max: 1 3x3 neighbors, 2 - 5x5 neighbs
		public int cuas_fin_range = 2; // for final filtering
		public int cuas_num_cycles = 25; // number of cycles of testing and removing bad targets // will get out earlier

		// Recalculate Motion Vectors before centered \"tracking camera\"
		public boolean cuas_recalc_mv = true; // Recalculate motion vectors before centered targets accumulation by masking far-from target areas
		public double cuas_recalc_mv_boost = 4.0; // Scale default number of correlation pairs for motion vectors calculation
		public double cuas_recalc_mv_r0 = 2.0; // Masking window parameters: for r <= r0, w = 1.0
		public double cuas_recalc_mv_r1 = 6.0; // Masking window parameters: for r >= r1, w = 0.0, r0<r<r1: w = 0.5(cos(PI(r-r0)/(r1-r0))+1)

		public int cuas_mul_samples = 3; // multiply number of samples in slow mode
		public int cuas_mul_offset = 5; // multiply correlation offset in slow mode

		@@ -2689,10 +2698,14 @@ min_str_neib_fpn 0.35
		"The number of correlation pairs to accumulate.");
		gd.addNumericField("Boost pairs for slow targets", this.cuas_boost_slow, 5,8,"",
		"If >1 and the motion vector is below tile_size/cuas_boost_slow, scale corr_pairs.");
		gd.addNumericField("Maximal MV to boost", this.cuas_boost_mv_lim, 5,8,"",
		"Do not boost if motion vector faster than this (before in code equiv 1.8 pix).");
		gd.addNumericField("Increase tracking camera exposure", this.cuas_boost_accum, 5,8,"",
		"If >1 increase tracking camera exposure (later - conditional).");
		gd.addNumericField("Boost pairs for weak targets", this.cuas_boost_mstr, 5,8,"",
		"Scale corr_pairs if motion strength is below.");
		"Scale corr_pairs if motion strength is below, regardless of speed.");
		gd.addNumericField("Never boost stronger", this.cuas_boost_xstr, 5,8,"",
		"Do not boost strong non-boosted, if confidence is higher.");
		gd.addNumericField("Pairs offset", this.cuas_corr_offset, 0,3,"scenes",
		"Offset between the correlation pairs");
		gd.addCheckbox ("Gaussian instead of Running Average", this.cuas_gaussian_ra,
		@@ -2715,6 +2728,16 @@ min_str_neib_fpn 0.35
		gd.addNumericField("Number of enhancement cycles", this.cuas_num_cycles, 0,3,"",
		"Number of cycles of testing and removing bad targets from compoetition with weaker neighbors.");

		gd.addMessage("=== Recalculate Motion Vectors before centered \"tracking camera\" ===");
		gd.addCheckbox ("Refine motion vectors", this.cuas_recalc_mv,
		"Recalculate motion vectors before centered targets accumulation by masking far-from target areas.");
		gd.addNumericField("Boost number of correlation pairs", this.cuas_recalc_mv_boost, 5,8,"x",
		"Scale default number of correlation pairs for motion vectors calculation.");
		gd.addNumericField("Center selection window R0 (inner)", this.cuas_recalc_mv_r0, 5,8,"pix",
		"Masking window parameters: for r <= r0, w = 1.0");
		gd.addNumericField("Center selection window R1 (outer)", this.cuas_recalc_mv_r1, 5,8,"pix",
		"Masking window parameters: for r >= r1, w = 0.0, r0<r<r1: w = 0.5(cos(PI(r-r0)/(r1-r0))+1).");

		gd.addMessage("=== Scale correlation parameters while detecting slow targets ===");
		gd.addNumericField("Scale number of correlation samples", this.cuas_mul_samples, 0,3,"",
		"Multiply number of samples in slow mode, keep center.");
		@@ -4349,8 +4372,10 @@ min_str_neib_fpn 0.35
		this.cuas_smooth = gd.getNextBoolean();
		this.cuas_corr_pairs = (int) gd.getNextNumber();
		this.cuas_boost_slow = gd.getNextNumber();
		this.cuas_boost_mv_lim = gd.getNextNumber();
		this.cuas_boost_accum = gd.getNextNumber();
		this.cuas_boost_mstr = gd.getNextNumber();
		this.cuas_boost_xstr = gd.getNextNumber();
		this.cuas_corr_offset = (int) gd.getNextNumber();
		this.cuas_gaussian_ra = gd.getNextBoolean();
		this.cuas_temporal_um = (int) gd.getNextNumber();
		@@ -4364,6 +4389,11 @@ min_str_neib_fpn 0.35
		this.cuas_fin_range = (int) gd.getNextNumber();
		this.cuas_num_cycles = (int) gd.getNextNumber();

		this.cuas_recalc_mv = gd.getNextBoolean();
		this.cuas_recalc_mv_boost = gd.getNextNumber();
		this.cuas_recalc_mv_r0 = gd.getNextNumber();
		this.cuas_recalc_mv_r1 = gd.getNextNumber();

		this.cuas_mul_samples = (int) gd.getNextNumber();
		this.cuas_mul_offset = (int) gd.getNextNumber();

		@@ -5649,8 +5679,10 @@ min_str_neib_fpn 0.35
		properties.setProperty(prefix+"cuas_smooth", this.cuas_smooth+""); // boolean
		properties.setProperty(prefix+"cuas_corr_pairs", this.cuas_corr_pairs+""); // int
		properties.setProperty(prefix+"cuas_boost_slow", this.cuas_boost_slow+""); // double
		properties.setProperty(prefix+"cuas_boost_mv_lim", this.cuas_boost_mv_lim+""); // double
		properties.setProperty(prefix+"cuas_boost_accum", this.cuas_boost_accum+""); // double
		properties.setProperty(prefix+"cuas_boost_mstr", this.cuas_boost_mstr+""); // double
		properties.setProperty(prefix+"cuas_boost_xstr", this.cuas_boost_xstr+""); // double
		properties.setProperty(prefix+"cuas_corr_offset", this.cuas_corr_offset+""); // int
		properties.setProperty(prefix+"cuas_gaussian_ra", this.cuas_gaussian_ra+""); // boolean
		properties.setProperty(prefix+"cuas_temporal_um", this.cuas_temporal_um+""); // int
		@@ -5664,6 +5696,11 @@ min_str_neib_fpn 0.35
		properties.setProperty(prefix+"cuas_fin_range", this.cuas_fin_range+""); // int
		properties.setProperty(prefix+"cuas_num_cycles", this.cuas_num_cycles+""); // int

		properties.setProperty(prefix+"cuas_recalc_mv", this.cuas_recalc_mv+""); // boolean
		properties.setProperty(prefix+"cuas_recalc_mv_boost", this.cuas_recalc_mv_boost+"");// double
		properties.setProperty(prefix+"cuas_recalc_mv_r0", this.cuas_recalc_mv_r0+""); // double
		properties.setProperty(prefix+"cuas_recalc_mv_r1", this.cuas_recalc_mv_r1+""); // double

		properties.setProperty(prefix+"cuas_mul_samples", this.cuas_mul_samples+""); // int
		properties.setProperty(prefix+"cuas_mul_offset", this.cuas_mul_offset+""); // int

		@@ -6884,8 +6921,10 @@ min_str_neib_fpn 0.35
		if (properties.getProperty(prefix+"cuas_smooth")!=null) this.cuas_smooth=Boolean.parseBoolean(properties.getProperty(prefix+"cuas_smooth"));
		if (properties.getProperty(prefix+"cuas_corr_pairs")!=null) this.cuas_corr_pairs=Integer.parseInt(properties.getProperty(prefix+"cuas_corr_pairs"));
		if (properties.getProperty(prefix+"cuas_boost_slow")!=null) this.cuas_boost_slow=Double.parseDouble(properties.getProperty(prefix+"cuas_boost_slow"));
		if (properties.getProperty(prefix+"cuas_boost_mv_lim")!=null) this.cuas_boost_mv_lim=Double.parseDouble(properties.getProperty(prefix+"cuas_boost_mv_lim"));
		if (properties.getProperty(prefix+"cuas_boost_accum")!=null) this.cuas_boost_accum=Double.parseDouble(properties.getProperty(prefix+"cuas_boost_accum"));
		if (properties.getProperty(prefix+"cuas_boost_mstr")!=null) this.cuas_boost_mstr=Double.parseDouble(properties.getProperty(prefix+"cuas_boost_mstr"));
		if (properties.getProperty(prefix+"cuas_boost_xstr")!=null) this.cuas_boost_xstr=Double.parseDouble(properties.getProperty(prefix+"cuas_boost_xstr"));
		if (properties.getProperty(prefix+"cuas_corr_offset")!=null) this.cuas_corr_offset=Integer.parseInt(properties.getProperty(prefix+"cuas_corr_offset"));
		if (properties.getProperty(prefix+"cuas_gaussian_ra")!=null) this.cuas_gaussian_ra=Boolean.parseBoolean(properties.getProperty(prefix+"cuas_gaussian_ra"));
		if (properties.getProperty(prefix+"cuas_temporal_um")!=null) this.cuas_temporal_um=Integer.parseInt(properties.getProperty(prefix+"cuas_temporal_um"));
		@@ -6899,6 +6938,11 @@ min_str_neib_fpn 0.35
		if (properties.getProperty(prefix+"cuas_fin_range")!=null) this.cuas_fin_range=Integer.parseInt(properties.getProperty(prefix+"cuas_fin_range"));
		if (properties.getProperty(prefix+"cuas_num_cycles")!=null) this.cuas_num_cycles=Integer.parseInt(properties.getProperty(prefix+"cuas_num_cycles"));

		if (properties.getProperty(prefix+"cuas_recalc_mv")!=null) this.cuas_recalc_mv=Boolean.parseBoolean(properties.getProperty(prefix+"cuas_recalc_mv"));
		if (properties.getProperty(prefix+"cuas_recalc_mv_boost")!=null) this.cuas_recalc_mv_boost=Double.parseDouble(properties.getProperty(prefix+"cuas_recalc_mv_boost"));
		if (properties.getProperty(prefix+"cuas_recalc_mv_r0")!=null) this.cuas_recalc_mv_r0=Double.parseDouble(properties.getProperty(prefix+"cuas_recalc_mv_r0"));
		if (properties.getProperty(prefix+"cuas_recalc_mv_r1")!=null) this.cuas_recalc_mv_r1=Double.parseDouble(properties.getProperty(prefix+"cuas_recalc_mv_r1"));

		if (properties.getProperty(prefix+"cuas_mul_samples")!=null) this.cuas_mul_samples=Integer.parseInt(properties.getProperty(prefix+"cuas_mul_samples"));
		if (properties.getProperty(prefix+"cuas_mul_offset")!=null) this.cuas_mul_offset=Integer.parseInt(properties.getProperty(prefix+"cuas_mul_offset"));

		@@ -8136,8 +8180,10 @@ min_str_neib_fpn 0.35
		imp.cuas_smooth = this.cuas_smooth;
		imp.cuas_corr_pairs = this.cuas_corr_pairs;
		imp.cuas_boost_slow = this.cuas_boost_slow;
		imp.cuas_boost_mv_lim = this.cuas_boost_mv_lim;
		imp.cuas_boost_accum = this.cuas_boost_accum;
		imp.cuas_boost_mstr = this.cuas_boost_mstr;
		imp.cuas_boost_xstr = this.cuas_boost_xstr;
		imp.cuas_corr_offset = this.cuas_corr_offset;
		imp.cuas_gaussian_ra = this.cuas_gaussian_ra;
		imp.cuas_temporal_um = this.cuas_temporal_um;
		@@ -8149,6 +8195,12 @@ min_str_neib_fpn 0.35
		imp.cuas_max_range = this.cuas_max_range;
		imp.cuas_fin_range = this.cuas_fin_range;
		imp.cuas_num_cycles = this.cuas_num_cycles;

		imp.cuas_recalc_mv = this.cuas_recalc_mv;
		imp.cuas_recalc_mv_boost = this.cuas_recalc_mv_boost;
		imp.cuas_recalc_mv_r0 = this.cuas_recalc_mv_r0;
		imp.cuas_recalc_mv_r1 = this.cuas_recalc_mv_r1;

		imp.cuas_mul_samples = this.cuas_mul_samples;
		imp.cuas_mul_offset = this.cuas_mul_offset;
		imp.cuas_speed_min = this.cuas_speed_min;

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