continue with eigen (413cd545) · Commits · Elphel / imagej-elphel

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

+93 −18

Original line number	Original line	Diff line number	Diff line
	@@ -2348,14 +2348,17 @@ public class ImageDtt extends ImageDttCPU {
	final double td_weight, // mix correlations accumulated in TD with		final double td_weight, // mix correlations accumulated in TD with
	final double td_neib_weight, // mix correlations accumulated in TD (neibs)		final double td_neib_weight, // mix correlations accumulated in TD (neibs)
	final double pd_weight, // correlations (post) accumulated in PD		final double pd_weight, // correlations (post) accumulated in PD

	final boolean td_nopd_only, // only use TD accumulated data if no safe PD is available for the tile.		final boolean td_nopd_only, // only use TD accumulated data if no safe PD is available for the tile.
	final boolean eig_use_neibs, // use correlation from 9 tiles with neibs, if single-tile fails		final boolean eig_use_neibs, // use correlation from 9 tiles with neibs, if single-tile fails
			final int eig_min_weaks, // = 4; minimal weak neighbors for a weak tile (too few - no averaging)
			final int eig_min_strongs, // minimal strong neighbors for strong tiles
			final double eig_disp_diff, // maximal disparity difference from the closest (by disparity) neighbor
	final boolean eig_remove_neibs, //remove weak (by-neibs) tiles if they have strong (by-single) neighbor		final boolean eig_remove_neibs, //remove weak (by-neibs) tiles if they have strong (by-single) neighbor
	final boolean eig_filt_other, // apply other before-eigen filters		final boolean eig_filt_other, // apply other before-eigen filters
	// final double min_str_nofpn, // = 0.25;
	final double eig_str_sum_nofpn,// = 0.8; // 5;		final double eig_str_sum_nofpn,// = 0.8; // 5;
	final double eig_str_neib_nofpn,// = 0.8; // 5;		final double eig_str_neib_nofpn,// = 0.8; // 5;
	// final double min_str_fpn, // = 0.25;
	final double eig_str_sum_fpn, // = 0.8; // 5;		final double eig_str_sum_fpn, // = 0.8; // 5;
	final double eig_str_neib_fpn, // = 0.8; // 5;		final double eig_str_neib_fpn, // = 0.8; // 5;
	final int min_neibs, // 2; // minimal number of strong neighbors (> min_str)		final int min_neibs, // 2; // minimal number of strong neighbors (> min_str)
	@@ -2365,7 +2368,7 @@ public class ImageDtt extends ImageDttCPU {

	final boolean neibs_nofpn_only, // consolidate neighbors for non-fpn tiles only!		final boolean neibs_nofpn_only, // consolidate neighbors for non-fpn tiles only!
	final boolean redo_both, // use average of neighbors for both pd,td if any of the center tile tests (td, pd) fails		final boolean redo_both, // use average of neighbors for both pd,td if any of the center tile tests (td, pd) fails
	final int min_num_neibs, // plus center, total number >= (min_num_neibs+1)
	final double scale_neibs_pd, // scale threshold for the pixel-domain average maximums		final double scale_neibs_pd, // scale threshold for the pixel-domain average maximums
	final double scale_neibs_td, // scale threshold for the transform-domain average maximums		final double scale_neibs_td, // scale threshold for the transform-domain average maximums
	final double scale_avg_weight, // reduce influence of the averaged correlations compared to the single-tile ones		final double scale_avg_weight, // reduce influence of the averaged correlations compared to the single-tile ones
	@@ -2379,7 +2382,6 @@ public class ImageDtt extends ImageDttCPU {
	final int threadsMax, // maximal number of threads to launch		final int threadsMax, // maximal number of threads to launch
	final int globalDebugLevel)		final int globalDebugLevel)
	{		{
	// final boolean
	// final boolean eigen_sub_min = false; // when calculating eigenvectors, subtract min from data, false - just skip		// final boolean eigen_sub_min = false; // when calculating eigenvectors, subtract min from data, false - just skip
	if (this.gpuQuad == null) {		if (this.gpuQuad == null) {
	System.out.println("clt_process_tl_interscene(): this.gpuQuad is null, bailing out");		System.out.println("clt_process_tl_interscene(): this.gpuQuad is null, bailing out");
	@@ -2497,6 +2499,7 @@ public class ImageDtt extends ImageDttCPU {
	final Thread[] threads = newThreadArray(threadsMax);		final Thread[] threads = newThreadArray(threadsMax);
	final AtomicInteger ai = new AtomicInteger(0);		final AtomicInteger ai = new AtomicInteger(0);
	final boolean [] used_td = new boolean [tilesX*tilesY]; // this tile had strong enough TD w/o neibs		final boolean [] used_td = new boolean [tilesX*tilesY]; // this tile had strong enough TD w/o neibs
			final boolean [] weak_tile = new boolean [tilesX*tilesY]; // this is a weak tile (only through consolidating neighbors)
	// all neibs with strong TD around them will be removed		// all neibs with strong TD around them will be removed
	// not using PD at all? always TD, then neibs?		// not using PD at all? always TD, then neibs?
	for (int ithread = 0; ithread < threads.length; ithread++) {		for (int ithread = 0; ithread < threads.length; ithread++) {
	@@ -2537,10 +2540,7 @@ public class ImageDtt extends ImageDttCPU {
	is_fpn = true;		is_fpn = true;
	}		}

	// double [][] corrs = new double [corrs_len + extra_len + extra_len_eig][]; // 1/17/2/18 +(0/1)
	double [][] corrs = new double [corrs_len + extra_len][]; // 1/17/2/18 +(0/1)		double [][] corrs = new double [corrs_len + extra_len][]; // 1/17/2/18 +(0/1)
	// int eigen_indx = (extra_len_eig > 0) ? (corrs_len + extra_len + extra_len_eig -1):-1;
	// int eigen_indx = (extra_len_eig > 0) ? (corrs_len + extra_len):-1;
	// copy correlation tiles from the GPU's floating point arrays		// copy correlation tiles from the GPU's floating point arrays
	double scale = 1.0/getNumSensors();		double scale = 1.0/getNumSensors();
	if (extra_sum) {		if (extra_sum) {
	@@ -2654,6 +2654,13 @@ public class ImageDtt extends ImageDttCPU {
	false, // boolean ignore_border, // only if fpn_mask != null - ignore tile if maximum touches fpn_mask		false, // boolean ignore_border, // only if fpn_mask != null - ignore tile if maximum touches fpn_mask
	debug_data, // double [][] debug_data, // null or double [1]		debug_data, // double [][] debug_data, // null or double [1]
	false); // boolean debug)		false); // boolean debug)
			weak_tile[nTile] = stats_mv != null;
			if (stats_mv != null) {
			stats_mv[2] -= eig_str_neib * scale_neibs_td;
			if (stats_mv[2] <= 0) {
			stats_mv = null;
			}
			}
	}		}
	if ((debug_data != null) && (debug_data[0] != null)) {		if ((debug_data != null) && (debug_data[0] != null)) {
	iCorrTile_index[nTile] = iCorrTile;		iCorrTile_index[nTile] = iCorrTile;
	@@ -2698,10 +2705,34 @@ public class ImageDtt extends ImageDttCPU {
	public void run() {		public void run() {
	TileNeibs tn = new TileNeibs(tilesX,tilesY);		TileNeibs tn = new TileNeibs(tilesX,tilesY);
	for (int nTile = ai.getAndIncrement(); nTile < tiles; nTile = ai.getAndIncrement()) {		for (int nTile = ai.getAndIncrement(); nTile < tiles; nTile = ai.getAndIncrement()) {
	if ((mv[nTile] != null) && !used_td[nTile]) { // is weak (by neibs)		boolean remove_tile = false;
			if (weak_tile[nTile]){
			int num_weak = 0;
			boolean has_strong = false;
			for (int dir = 0; dir < TileNeibs.DIRS; dir++) {
			int nTile1 = tn.getNeibIndex(nTile, dir);
			if (nTile1 >= 0) {
			if (used_td[nTile1]) {
			has_strong = true;
			break;
			} else if (weak_tile[nTile1]) {
			num_weak++;
			}
			}
			}
			remove_tile \|= (has_strong \|\| (num_weak < eig_min_weaks));
			} else if (used_td[nTile]) {
			int num_strong = 0;
	for (int dir = 0; dir < TileNeibs.DIRS; dir++) {		for (int dir = 0; dir < TileNeibs.DIRS; dir++) {
	int nTile1 = tn.getNeibIndex(nTile, dir);		int nTile1 = tn.getNeibIndex(nTile, dir);
	if ((nTile1 >= 0) && used_td[nTile1]) {		if ((nTile1 >= 0) && (used_td[nTile1])) {
			num_strong++;
			}
			}
			remove_tile \|= (num_strong < eig_min_strongs);
			}

			if (remove_tile) { // any of 3 reasons above
	mv[nTile] = null;		mv[nTile] = null;
	if (pxd != null) {		if (pxd != null) {
	pxd[nTile] = null;		pxd[nTile] = null;
	@@ -2711,16 +2742,58 @@ public class ImageDtt extends ImageDttCPU {
	dcorr_tiles[iCorrTile][eigen_indx+1] = null;		dcorr_tiles[iCorrTile][eigen_indx+1] = null;
	dcorr_tiles[iCorrTile][eigen_indx+3] = null;		dcorr_tiles[iCorrTile][eigen_indx+3] = null;
	}		}
	break;
	}		}
	}		}
	}		}
			};
			}
			startAndJoin(threads);
			if (eig_disp_diff > 0) {
			final boolean [] remove_tiles = new boolean[tilesX*tilesY];
			ai.set(0);
			for (int ithread = 0; ithread < threads.length; ithread++) {
			threads[ithread] = new Thread() {
			@Override
			public void run() {
			TileNeibs tn = new TileNeibs(tilesX,tilesY);
			for (int nTile = ai.getAndIncrement(); nTile < tiles; nTile = ai.getAndIncrement()) if ((mv[nTile] != null) && (pXpYD[nTile] != null)) {
			double min_diff = eig_disp_diff + 1.0;
			double disp_c = pxd[nTile][2];
			for (int dir = 0; dir < TileNeibs.DIRS; dir++) {
			int nTile1 = tn.getNeibIndex(nTile, dir);
			if ((nTile1 >= 0) && (pxd[nTile1]!= null) && !Double.isNaN(pxd[nTile1][2])) {
			min_diff = Math.min(Math.abs(pxd[nTile1][2]-disp_c), min_diff);
			}
			}
			remove_tiles[nTile] \|= (min_diff > eig_disp_diff);
			}
			}
			};
			}
			startAndJoin(threads);
			ai.set(0);
			for (int ithread = 0; ithread < threads.length; ithread++) {
			threads[ithread] = new Thread() {
			@Override
			public void run() {
			for (int nTile = ai.getAndIncrement(); nTile < tiles; nTile = ai.getAndIncrement()) if (remove_tiles[nTile]) {
			mv[nTile] = null;
			if (pxd != null) {
			pxd[nTile] = null;
			}
			if (iCorrTile_index != null) {
			int iCorrTile = iCorrTile_index[nTile];
			dcorr_tiles[iCorrTile][eigen_indx+1] = null;
			dcorr_tiles[iCorrTile][eigen_indx+3] = null;
			}
	}		}
	}		}
	};		};
	}		}
	startAndJoin(threads);		startAndJoin(threads);
	}		}

			}
	// Reduce weight if differs much from average of 8 neighbors, large disparity, remove too few neibs		// Reduce weight if differs much from average of 8 neighbors, large disparity, remove too few neibs
	final double scale_num_neib = ((weight_zero_neibs >= 0) && (weight_zero_neibs < 1.0)) ? (weight_zero_neibs * 8/(1.0 - weight_zero_neibs)): 0.0;		final double scale_num_neib = ((weight_zero_neibs >= 0) && (weight_zero_neibs < 1.0)) ? (weight_zero_neibs * 8/(1.0 - weight_zero_neibs)): 0.0;
	if (eig_filt_other) {		if (eig_filt_other) {
	@@ -2792,6 +2865,8 @@ public class ImageDtt extends ImageDttCPU {
	startAndJoin(threads);		startAndJoin(threads);
	return coord_motion;		return coord_motion;
	}		}


	// using most of the ImageDttCPU.clt_process_tl_correlations		// using most of the ImageDttCPU.clt_process_tl_correlations
	public void clt_process_tl_correlations( // convert to pixel domain and process correlations already prepared in fcorr_td and/or fcorr_combo_td		public void clt_process_tl_correlations( // convert to pixel domain and process correlations already prepared in fcorr_td and/or fcorr_combo_td
	final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others		final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others

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

+83 −74

Original line number	Original line	Diff line number	Diff line
	@@ -534,7 +534,7 @@ public class Interscene {
	boolean use_lma_dsi = clt_parameters.imp.use_lma_dsi;		boolean use_lma_dsi = clt_parameters.imp.use_lma_dsi;
	double [] reduced_strength = new double[1];		double [] reduced_strength = new double[1];
	double avg_z = quadCLTs[ref_index].getAverageZ(true); // use lma		double avg_z = quadCLTs[ref_index].getAverageZ(true); // use lma
	double [] lma_rms = new double[clt_parameters.imp.eig_use? 4 : 2]; // [2];		double [] lma_rms = new double[clt_parameters.imp.eig_use? 6 : 4]; // [2];
	// use combo if second pass?		// use combo if second pass?
	if (min_ref_str > 0.0) {		if (min_ref_str > 0.0) {
	reliable_ref = quadCLTs[ref_index].getReliableTiles( // will be null if does not exist.		reliable_ref = quadCLTs[ref_index].getReliableTiles( // will be null if does not exist.
	@@ -683,20 +683,20 @@ public class Interscene {
	);		);
	rmse_stats.add(lma_rms[0]);		rmse_stats.add(lma_rms[0]);
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {
	rmse_stats_metric.add(lma_rms[2]);		rmse_stats_metric.add(lma_rms[4]);
	}		}
	if (debugLevel > -3) {		if (debugLevel > -3) {
	System.out.print("invertInitialOrientation(): scene "+scene_index+" (of "+ quadCLTs.length+") "+		System.out.println("invertInitialOrientation(): scene "+scene_index+" (of "+ quadCLTs.length+") "+
	quadCLTs[ref_index].getImageName() + "/" + quadCLTs[scene_index].getImageName()+		quadCLTs[ref_index].getImageName() + "/" + quadCLTs[scene_index].getImageName()+
	" Done. RMS="+lma_rms[0]+		" Done. Weight = "+lma_rms[2]+", number="+lma_rms[3]);
			System.out.print("RMS="+lma_rms[0]+
	", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());		", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=6)) {
	System.out.print(". RMS="+lma_rms[2]+		System.out.print(". Pixel RMS="+lma_rms[4]+
	"pix, maximal so far was "+rmse_stats_metric.getMax()+		"pix, maximal so far was "+rmse_stats_metric.getMax()+
	"pix, average was "+rmse_stats_metric.getAverage()+"pix.");		"pix, average was "+rmse_stats_metric.getAverage()+"pix.");
	}		}
	System.out.println();		System.out.println();

	}		}
	} // for (int scene_index = ref_index; scene_index <= last_index; scene_index++) {		} // for (int scene_index = ref_index; scene_index <= last_index; scene_index++) {

	@@ -783,15 +783,16 @@ public class Interscene {
	adjusted_xyzatr_dt[1]); // ZERO3 // ers_scene.getErsATR_dt()		adjusted_xyzatr_dt[1]); // ZERO3 // ers_scene.getErsATR_dt()
	rmse_stats.add(lma_rms[0]);		rmse_stats.add(lma_rms[0]);
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {
	rmse_stats_metric.add(lma_rms[2]);		rmse_stats_metric.add(lma_rms[4]);
	}		}
	if (debugLevel > -3) {		if (debugLevel > -3) {
	System.out.print("Pass multi scene "+fpn_pairs[ipair][0]+" (of "+ quadCLTs.length+") "+		System.out.println("Pass multi scene "+fpn_pairs[ipair][0]+" (of "+ quadCLTs.length+") "+
	quadCLTs[fpn_pairs[ipair][1]].getImageName() + "/" + quadCLTs[fpn_pairs[ipair][0]].getImageName()+		quadCLTs[fpn_pairs[ipair][1]].getImageName() + "/" + quadCLTs[fpn_pairs[ipair][0]].getImageName()+
	" Done. RMS="+lma_rms[0]+		" Done. Weight = "+lma_rms[2]+", number="+lma_rms[3]);
			System.out.print("RMS="+lma_rms[0]+
	", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());		", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=6)) {
	System.out.print(". RMS="+lma_rms[2]+		System.out.print(". RMS="+lma_rms[4]+
	"pix, maximal so far was "+rmse_stats_metric.getMax()+		"pix, maximal so far was "+rmse_stats_metric.getMax()+
	"pix, average was "+rmse_stats_metric.getAverage()+"pix.");		"pix, average was "+rmse_stats_metric.getAverage()+"pix.");
	}		}
	@@ -866,7 +867,7 @@ public class Interscene {
	System.out.println("*** setInitialOrientationsIms(): clt_parameters.ilp.ilma_3d is TRUE. You may want to disable it when using IMS");		System.out.println("*** setInitialOrientationsIms(): clt_parameters.ilp.ilma_3d is TRUE. You may want to disable it when using IMS");
	}		}

	double [] lma_rms = new double[clt_parameters.imp.eig_use? 4 : 2]; // [2];		double [] lma_rms = new double[clt_parameters.imp.eig_use? 6 : 4]; // [2];

	int tilesX = quadCLTs[ref_index].getTileProcessor().getTilesX();		int tilesX = quadCLTs[ref_index].getTileProcessor().getTilesX();
	int tilesY = quadCLTs[ref_index].getTileProcessor().getTilesY();		int tilesY = quadCLTs[ref_index].getTileProcessor().getTilesY();
	@@ -1202,15 +1203,16 @@ public class Interscene {
	);		);
	rmse_stats.add(lma_rms[0]);		rmse_stats.add(lma_rms[0]);
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {
	rmse_stats_metric.add(lma_rms[2]);		rmse_stats_metric.add(lma_rms[4]);
	}		}
	if (debugLevel > -3) {		if (debugLevel > -3) {
	System.out.print("Pass multi scene "+scene_index+" (of "+ quadCLTs.length+") "+		System.out.println("Pass multi scene "+scene_index+" (of "+ quadCLTs.length+") "+
	quadCLTs[ref_index].getImageName() + "/" + scene_QuadClt.getImageName()+		quadCLTs[ref_index].getImageName() + "/" + scene_QuadClt.getImageName()+
	" Done. RMS="+lma_rms[0]+		" Done. Weight = "+lma_rms[2]+", number="+lma_rms[3]);
			System.out.print("RMS="+lma_rms[0]+
	", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());		", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=6)) {
	System.out.print(". RMS="+lma_rms[2]+		System.out.print(". Pixel RMS="+lma_rms[4]+
	"pix, maximal so far was "+rmse_stats_metric.getMax()+		"pix, maximal so far was "+rmse_stats_metric.getMax()+
	"pix, average was "+rmse_stats_metric.getAverage()+"pix.");		"pix, average was "+rmse_stats_metric.getAverage()+"pix.");
	}		}
	@@ -1310,15 +1312,16 @@ public class Interscene {
	adjusted_xyzatr_dt[1]); // ZERO3 // ers_scene.getErsATR_dt()		adjusted_xyzatr_dt[1]); // ZERO3 // ers_scene.getErsATR_dt()
	rmse_stats.add(lma_rms[0]);		rmse_stats.add(lma_rms[0]);
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {
	rmse_stats_metric.add(lma_rms[2]);		rmse_stats_metric.add(lma_rms[4]);
	}		}
	if (debugLevel > -3) {		if (debugLevel > -3) {
	System.out.print("Pass multi scene "+fpn_pairs[ipair][0]+" (of "+ quadCLTs.length+") "+		System.out.println("Pass multi scene "+fpn_pairs[ipair][0]+" (of "+ quadCLTs.length+") "+
	quadCLTs[fpn_pairs[ipair][1]].getImageName() + "/" + quadCLTs[fpn_pairs[ipair][0]].getImageName()+		quadCLTs[fpn_pairs[ipair][1]].getImageName() + "/" + quadCLTs[fpn_pairs[ipair][0]].getImageName()+
	" Done. RMS="+lma_rms[0]+		" Done. Weight = "+lma_rms[2]+", number="+lma_rms[3]);
			System.out.print("RMS="+lma_rms[0]+
	", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());		", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=6)) {
	System.out.print(". RMS="+lma_rms[2]+		System.out.print(". Pixel RMS="+lma_rms[4]+
	"pix, maximal so far was "+rmse_stats_metric.getMax()+		"pix, maximal so far was "+rmse_stats_metric.getMax()+
	"pix, average was "+rmse_stats_metric.getAverage()+"pix.");		"pix, average was "+rmse_stats_metric.getAverage()+"pix.");
	}		}
	@@ -1827,15 +1830,16 @@ public class Interscene {
	);		);
	rmse_stats.add(lma_rms[0]);		rmse_stats.add(lma_rms[0]);
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {
	rmse_stats_metric.add(lma_rms[2]);		rmse_stats_metric.add(lma_rms[4]);
	}		}
	if (debugLevel > -3) {		if (debugLevel > -3) {
	System.out.print("Pass multi scene "+scene_index+" (of "+ quadCLTs.length+") "+		System.out.println("Pass multi scene "+scene_index+" (of "+ quadCLTs.length+") "+
	quadCLTs[ref_index].getImageName() + "/" + scene_QuadClt.getImageName()+		quadCLTs[ref_index].getImageName() + "/" + scene_QuadClt.getImageName()+
	" Done. RMS="+lma_rms[0]+		" Done. Weight = "+lma_rms[2]+", number="+lma_rms[3]);
			System.out.print("RMS="+lma_rms[0]+
	", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());		", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=6)) {
	System.out.print(". RMS="+lma_rms[2]+		System.out.print(". Pixel RMS="+lma_rms[4]+
	"pix, maximal so far was "+rmse_stats_metric.getMax()+		"pix, maximal so far was "+rmse_stats_metric.getMax()+
	"pix, average was "+rmse_stats_metric.getAverage()+"pix.");		"pix, average was "+rmse_stats_metric.getAverage()+"pix.");
	}		}
	@@ -2362,7 +2366,7 @@ public class Interscene {
	boolean test_adjust = debugLevel > 1000;		boolean test_adjust = debugLevel > 1000;
	while (test_adjust) {		while (test_adjust) {
	int [] test_pair = {ref_index, 0};		int [] test_pair = {ref_index, 0};
	double [] test_lma_rms = new double[clt_parameters.imp.eig_use? 4 : 2]; // [2];		double [] test_lma_rms = new double[clt_parameters.imp.eig_use? 6 : 4]; // [2];
	TpTask[][] tp_tasks_test_rel_ref = new TpTask[2][];		TpTask[][] tp_tasks_test_rel_ref = new TpTask[2][];
	double [][] test_xyzatr = adjustDiffPairsLMAInterscene( // compare two scenes, first may be reference, use motion blur		double [][] test_xyzatr = adjustDiffPairsLMAInterscene( // compare two scenes, first may be reference, use motion blur
	clt_parameters, //CLTParameters clt_parameters,		clt_parameters, //CLTParameters clt_parameters,
	@@ -2468,7 +2472,7 @@ public class Interscene {
	dxyzatr_dt[nscene]		dxyzatr_dt[nscene]
	);		);
	} else { // if (nscene == ref_index)		} else { // if (nscene == ref_index)
	double [] lma_rms = new double[clt_parameters.imp.eig_use? 4 : 2]; // [2];		double [] lma_rms = new double[clt_parameters.imp.eig_use? 6 : 4]; // [2];
	double [][] initial_pose = scenes_xyzatr[nscene].clone();		double [][] initial_pose = scenes_xyzatr[nscene].clone();
	boolean adjust_OK = false;		boolean adjust_OK = false;
	if (est_shift < min_max[0]) {		if (est_shift < min_max[0]) {
	@@ -2605,15 +2609,16 @@ public class Interscene {

	rmse_stats.add(lma_rms[0]);		rmse_stats.add(lma_rms[0]);
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {
	rmse_stats_metric.add(lma_rms[2]);		rmse_stats_metric.add(lma_rms[4]);
	}		}
	if (debugLevel > -3) {		if (debugLevel > -3) {
	System.out.print("reAdjustPairsLMAInterscene "+nscene+" (of "+ quadCLTs.length+") "+		System.out.println("reAdjustPairsLMAInterscene "+nscene+" (of "+ quadCLTs.length+") "+
	quadCLTs[ref_index].getImageName() + "/" + ts+		quadCLTs[ref_index].getImageName() + "/" + ts+
	" Done. RMS="+lma_rms[0]+		" Done. Weight = "+lma_rms[2]+", number="+lma_rms[3]);
			System.out.print("RMS="+lma_rms[0]+
	", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());		", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=6)) {
	System.out.print(". RMS="+lma_rms[2]+		System.out.print(". Pixel RMS="+lma_rms[4]+
	"pix, maximal so far was "+rmse_stats_metric.getMax()+		"pix, maximal so far was "+rmse_stats_metric.getMax()+
	"pix, average was "+rmse_stats_metric.getAverage()+"pix.");		"pix, average was "+rmse_stats_metric.getAverage()+"pix.");
	}		}
	@@ -2674,7 +2679,7 @@ public class Interscene {
	" being too close to reference "+ref_index+		" being too close to reference "+ref_index+
	", using scene "+fpn_pairs[ipair][1]+" as a reference");		", using scene "+fpn_pairs[ipair][1]+" as a reference");
	}		}
	double [] lma_rms = new double[clt_parameters.imp.eig_use? 4 : 2]; // [2];		double [] lma_rms = new double[clt_parameters.imp.eig_use? 6 : 4]; // [2];
	TpTask[][] tp_tasks_rel_ref = new TpTask[2][];		TpTask[][] tp_tasks_rel_ref = new TpTask[2][];
	double [][] rel_xyzatr = adjustDiffPairsLMAInterscene( // compare two scenes, first may be reference, use motion blur		double [][] rel_xyzatr = adjustDiffPairsLMAInterscene( // compare two scenes, first may be reference, use motion blur
	clt_parameters, //CLTParameters clt_parameters,		clt_parameters, //CLTParameters clt_parameters,
	@@ -2726,15 +2731,16 @@ public class Interscene {
	adjusted_xyzatr_dt[1]);		adjusted_xyzatr_dt[1]);
	rmse_stats.add(lma_rms[0]);		rmse_stats.add(lma_rms[0]);
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {
	rmse_stats_metric.add(lma_rms[2]);		rmse_stats_metric.add(lma_rms[4]);
	}		}
	if (debugLevel > -3) {		if (debugLevel > -3) {
	System.out.print("reAdjustPairsLMAInterscene "+fpn_pairs[ipair][0]+" (of "+ quadCLTs.length+") "+		System.out.println("reAdjustPairsLMAInterscene "+fpn_pairs[ipair][0]+" (of "+ quadCLTs.length+") "+
	quadCLTs[fpn_pairs[ipair][1]].getImageName() + "/" + quadCLTs[fpn_pairs[ipair][0]].getImageName()+		quadCLTs[fpn_pairs[ipair][1]].getImageName() + "/" + quadCLTs[fpn_pairs[ipair][0]].getImageName()+
	" Done. RMS="+lma_rms[0]+		" Done. Weight = "+lma_rms[2]+", number="+lma_rms[3]);
			System.out.print("RMS="+lma_rms[0]+
	", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());		", maximal so far was "+rmse_stats.getMax()+", average was "+rmse_stats.getAverage());
	if ((rmse_stats_metric != null) && (lma_rms.length >=4)) {		if ((rmse_stats_metric != null) && (lma_rms.length >=6)) {
	System.out.print(". RMS="+lma_rms[2]+		System.out.print(". Pixel RMS="+lma_rms[4]+
	"pix, maximal so far was "+rmse_stats_metric.getMax()+		"pix, maximal so far was "+rmse_stats_metric.getMax()+
	"pix, average was "+rmse_stats_metric.getAverage()+"pix.");		"pix, average was "+rmse_stats_metric.getAverage()+"pix.");
	}		}
	@@ -2748,7 +2754,7 @@ public class Interscene {
	if (test_adjust1) {		if (test_adjust1) {
	int [] test_pair = {0, ref_index};		int [] test_pair = {0, ref_index};
	while (test_adjust1) {		while (test_adjust1) {
	double [] test_lma_rms = new double[clt_parameters.imp.eig_use? 4 : 2]; // [2];		double [] test_lma_rms = new double[clt_parameters.imp.eig_use? 6 : 4]; // [2];
	TpTask[][] tp_tasks_test_rel_ref = new TpTask[2][];		TpTask[][] tp_tasks_test_rel_ref = new TpTask[2][];
	System.out.println("test_adjust scene = "+test_pair[0]+", reference="+test_pair[1]);		System.out.println("test_adjust scene = "+test_pair[0]+", reference="+test_pair[1]);
	double [][] test_xyzatr = adjustDiffPairsLMAInterscene( // compare two scenes, first may be reference, use motion blur		double [][] test_xyzatr = adjustDiffPairsLMAInterscene( // compare two scenes, first may be reference, use motion blur
	@@ -3540,18 +3546,22 @@ public class Interscene {
	if ((rms_out != null) && (intersceneLma.getLastRms() != null)) {		if ((rms_out != null) && (intersceneLma.getLastRms() != null)) {
	rms_out[0] = intersceneLma.getLastRms()[0];		rms_out[0] = intersceneLma.getLastRms()[0];
	rms_out[1] = intersceneLma.getLastRms()[1];		rms_out[1] = intersceneLma.getLastRms()[1];
			if (rms_out.length >=2) {
			rms_out[2] = intersceneLma.getSumWeights();
			rms_out[3] = intersceneLma.getNumDefined();

	if (rms_out.length >=4) {		if (rms_out.length >=4) {
	if (intersceneLma.isEigenNormalized()) {		if (intersceneLma.isEigenNormalized()) {
	double [] rms_metric = intersceneLma.calcRMS(true);		double [] rms_metric = intersceneLma.calcRMS(true);
	rms_out[2] = rms_metric[0];		rms_out[4] = rms_metric[0];
	rms_out[3] = rms_metric[1];		rms_out[5] = rms_metric[1];

	} else {		} else {
	rms_out[2] = Double.NaN;		rms_out[4] = Double.NaN;
	rms_out[3] = Double.NaN;		rms_out[5] = Double.NaN;
			}
	}		}
	}		}

	//if (lmaResult < 0) { last_rms[0]		//if (lmaResult < 0) { last_rms[0]
	}		}
	if (max_rms > 0.0) {		if (max_rms > 0.0) {
	@@ -4308,7 +4318,6 @@ public class Interscene {
	fpn_offsets, // final double [][] fpn_offsets, // null, or per-tile X,Y offset to be blanked		fpn_offsets, // final double [][] fpn_offsets, // null, or per-tile X,Y offset to be blanked
	fpn_radius, // final double fpn_radius, // radius to be blanked around FPN offset center		fpn_radius, // final double fpn_radius, // radius to be blanked around FPN offset center
	fpn_ignore_border, // final boolean fpn_ignore_border, // only if fpn_mask != null - ignore tile if maximum touches fpn_mask		fpn_ignore_border, // final boolean fpn_ignore_border, // only if fpn_mask != null - ignore tile if maximum touches fpn_mask
	// motion_vectors, // final double [][][] motion_vectors, // [tilesY*tilesX][][] -> [][][num_sel_sensors+1][2]
	clt_parameters.imp.run_poly, // final boolean run_poly, // polynomial max, if false - centroid		clt_parameters.imp.run_poly, // final boolean run_poly, // polynomial max, if false - centroid
	use_partial, // final boolean use_partial, // find motion vectors for individual pairs, false - for sum only		use_partial, // final boolean use_partial, // find motion vectors for individual pairs, false - for sum only
	clt_parameters.imp.centroid_radius,// final double centroid_radius, // 0 - use all tile, >0 - cosine window around local max		clt_parameters.imp.centroid_radius,// final double centroid_radius, // 0 - use all tile, >0 - cosine window around local max
	@@ -4318,12 +4327,13 @@ public class Interscene {
	clt_parameters.imp.pd_weight, // final double pd_weight, // correlations (post) accumulated in PD		clt_parameters.imp.pd_weight, // final double pd_weight, // correlations (post) accumulated in PD
	clt_parameters.imp.td_nopd_only, // final boolean td_nopd_only , // only use TD accumulated data if no safe PD is available for the tile.		clt_parameters.imp.td_nopd_only, // final boolean td_nopd_only , // only use TD accumulated data if no safe PD is available for the tile.
	clt_parameters.imp.eig_use_neibs, // final boolean eig_use_neibs, // use correlation from 9 tiles with neibs, if single-tile fails		clt_parameters.imp.eig_use_neibs, // final boolean eig_use_neibs, // use correlation from 9 tiles with neibs, if single-tile fails
			clt_parameters.imp.eig_min_weaks, // final int eig_min_weaks, // = 4; minimal weak neighbors for a weak tile (too few - no averaging)
			clt_parameters.imp.eig_min_strongs,// final int eig_min_strongs, // minimal strong neighbors for strong tiles
			clt_parameters.imp.eig_disp_diff, // final double eig_disp_diff, // maximal disparity difference from the closest (by disparity) neighbor
	clt_parameters.imp.eig_remove_neibs,//final boolean eig_remove_neibs, //remove weak (by-neibs) tiles if they have strong (by-single) neighbor		clt_parameters.imp.eig_remove_neibs,//final boolean eig_remove_neibs, //remove weak (by-neibs) tiles if they have strong (by-single) neighbor
	clt_parameters.imp.eig_filt_other, // final boolean eig_filt_other, // apply other before-eigen filters		clt_parameters.imp.eig_filt_other, // final boolean eig_filt_other, // apply other before-eigen filters
	// min_str, // final double min_str_nofpn, // = 0.25;
	eig_str_sum, // final double eig_str_sum_nofpn, // = 0.8; // 5;		eig_str_sum, // final double eig_str_sum_nofpn, // = 0.8; // 5;
	eig_str_neib, // final double eig_str_neib_nofpn,		eig_str_neib, // final double eig_str_neib_nofpn,
	// clt_parameters.imp.min_str_fpn, // final double min_str, // = 0.25;
	clt_parameters.imp.eig_str_sum_fpn,// final double eig_str_sum_fpn, // = 0.8; // 5;		clt_parameters.imp.eig_str_sum_fpn,// final double eig_str_sum_fpn, // = 0.8; // 5;
	clt_parameters.imp.eig_str_neib_fpn,//final double eig_str_neib_fpn,		clt_parameters.imp.eig_str_neib_fpn,//final double eig_str_neib_fpn,
	clt_parameters.imp.min_neibs, // final int min_neibs, // 2; // minimal number of strong neighbors (> min_str)		clt_parameters.imp.min_neibs, // final int min_neibs, // 2; // minimal number of strong neighbors (> min_str)
	@@ -4332,7 +4342,6 @@ public class Interscene {
	clt_parameters.imp.half_avg_diff, // final double half_avg_diff, // 0.2; // when L2 of x,y difference from average of neibs - reduce twice		clt_parameters.imp.half_avg_diff, // final double half_avg_diff, // 0.2; // when L2 of x,y difference from average of neibs - reduce twice
	neibs_nofpn_only, // final boolean neibs_nofpn_only, // consolidate neighbors fot non-fpn tiles only!		neibs_nofpn_only, // final boolean neibs_nofpn_only, // consolidate neighbors fot non-fpn tiles only!
	redo_both, // final boolean redo_both, // use average of neighbors for both pd,td if any of the center tile tests (td, pd) fails		redo_both, // final boolean redo_both, // use average of neighbors for both pd,td if any of the center tile tests (td, pd) fails
	min_num_neibs, // final int min_num_neibs, // plus center, total number >= (min_num_neibs+1)
	scale_neibs_pd, // final double scale_neibs_pd, // scale threshold for the pixel-domain average maximums		scale_neibs_pd, // final double scale_neibs_pd, // scale threshold for the pixel-domain average maximums
	scale_neibs_td, // final double scale_neibs_td, // scale threshold for the transform-domain average maximums		scale_neibs_td, // final double scale_neibs_td, // scale threshold for the transform-domain average maximums
	scale_avg_weight, // final double scale_avg_weight, // reduce influence of the averaged correlations compared to the single-tile ones		scale_avg_weight, // final double scale_avg_weight, // reduce influence of the averaged correlations compared to the single-tile ones

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