handling zero eigenvalues (41d614cb) · Commits · Elphel / imagej-elphel

src/main/java/EyesisCorrectionParameters.java

+12 −2

src/main/java/SuperTiles.java

+50 −39

Original line number	Original line	Diff line number	Diff line
	@@ -1168,7 +1168,6 @@ public class SuperTiles{


	public void processPlanes2(		public void processPlanes2(

	final boolean [] selected, // or null		final boolean [] selected, // or null
	final double min_disp,		final double min_disp,
	final boolean invert_disp, // use 1/disparity		final boolean invert_disp, // use 1/disparity
	@@ -1177,6 +1176,7 @@ public class SuperTiles{
	final double plTargetEigen, // = 0.1; // Remove outliers until main axis eigenvalue (possibly scaled by plDispNorm) gets below		final double plTargetEigen, // = 0.1; // Remove outliers until main axis eigenvalue (possibly scaled by plDispNorm) gets below
	final double plFractOutliers, // = 0.3; // Maximal fraction of outliers to remove		final double plFractOutliers, // = 0.3; // Maximal fraction of outliers to remove
	final int plMaxOutliers, // = 20; // Maximal number of outliers to remove		final int plMaxOutliers, // = 20; // Maximal number of outliers to remove
			final boolean plPreferDisparity, // Always start with disparity-most axis (false - lowest eigenvalue)
	final GeometryCorrection geometryCorrection,		final GeometryCorrection geometryCorrection,
	final boolean correct_distortions,		final boolean correct_distortions,
	final int debugLevel,		final int debugLevel,
	@@ -1262,27 +1262,19 @@ public class SuperTiles{
	}		}
	}		}
	planes[nsTile] = null;		planes[nsTile] = null;
	if (sw >0){		if (sw >0){ // there are some non-zero tiles, process them (all points, not clustered by disparity value)
	ArrayList<TilePlanes.PlaneData> st_planes = new ArrayList<TilePlanes.PlaneData>();		ArrayList<TilePlanes.PlaneData> st_planes = new ArrayList<TilePlanes.PlaneData>();
	// int dl = ((nsTile >= debug_stile-1) && (nsTile <= debug_stile+1) ) ? 1 : 0;
	// int dl = ((stileY == 17) && (stileX > 4)) ? 1 : 0;
	// int dl = (stileY >= 0) ? 1 : 0;
	int dl1 = (nsTile == debug_stile) ? 3 : 0;		int dl1 = (nsTile == debug_stile) ? 3 : 0;
	// int dl = (nsTile == debug_stile) ? 3 : 0;
	// int dl = ((stileY >= 15) && (stileY <= 18) && (stileX >= 5) && (stileX <= 31)) ? 1 : 0;
	// int dl = ((stileY == 16) && (stileX == 27) ) ? 3 : 0;
	int dl = (nsTile == debug_stile) ? 3 : 0;		int dl = (nsTile == debug_stile) ? 3 : 0;
	// int debugLevel1 = ((sTileXY[0] == 27) && (sTileXY[1] == 16))? 1: 0; // check why v[0][0] <0


	boolean [] sel_all = stSel.clone();		boolean [] sel_all = stSel.clone();
	TilePlanes.PlaneData pd = tpl.getPlane(		TilePlanes.PlaneData pd = tpl.getPlane(
	sTiles,		sTiles,
	stDisparity,		stDisparity,
	stStrength,		stStrength,
	sel_all,		sel_all,
			plPreferDisparity,
	0); // debugLevel);		0); // debugLevel);
	if (pd != null) {		if (pd != null) { // not too few points, probably
	//correct_distortions		//correct_distortions
	double swc_common = pd.getWeight();		double swc_common = pd.getWeight();
	if (dl > 0) {		if (dl > 0) {
	@@ -1301,19 +1293,11 @@ public class SuperTiles{
	// now try to remove outliers		// now try to remove outliers
	int max_outliers = (int) Math.round(pd.getNumPoints() * plFractOutliers);		int max_outliers = (int) Math.round(pd.getNumPoints() * plFractOutliers);
	if (max_outliers > plMaxOutliers) max_outliers = plMaxOutliers;		if (max_outliers > plMaxOutliers) max_outliers = plMaxOutliers;
	/*
	double targetV = plTargetEigen;
	double z0 = pd.getZxy()[0];
	if ((plTargetEigen > 0.0) && (z0 > plDispNorm)) {
	double dd = (plDispNorm + z0)/ plDispNorm; // > 1
	targetV = dd dd; // > original
	}
	*/
	double targetV = corrMaxEigen(		double targetV = corrMaxEigen(
	plTargetEigen,		plTargetEigen,
	plDispNorm,		plDispNorm,
	pd);		pd);
	if (pd.getValues()[0] > targetV) {		if (pd.getValue() > targetV) {
	pd = tpl.removePlaneOutliers(		pd = tpl.removePlaneOutliers(
	pd,		pd,
	sTiles,		sTiles,
	@@ -1323,7 +1307,9 @@ public class SuperTiles{
	targetV, // double targetEigen, // target eigenvalue for primary axis (is disparity-dependent, so is non-constant)		targetV, // double targetEigen, // target eigenvalue for primary axis (is disparity-dependent, so is non-constant)
	max_outliers, // int maxRemoved, // maximal number of tiles to remove (not a constant)		max_outliers, // int maxRemoved, // maximal number of tiles to remove (not a constant)
	plMinPoints, // int minLeft, // minimal number of tiles to keep		plMinPoints, // int minLeft, // minimal number of tiles to keep
			plPreferDisparity,
	dl1); // 0); // debugLevel);		dl1); // 0); // debugLevel);
			if (pd == null) continue;
	if (dl > 0) {		if (dl > 0) {
	if (swc_common > 0.3) { // 1.0) {		if (swc_common > 0.3) { // 1.0) {
	System.out.println("Removed outliers["+nsTile+"]"+		System.out.println("Removed outliers["+nsTile+"]"+
	@@ -1350,9 +1336,9 @@ public class SuperTiles{
	norm_xyz[0]+", "+norm_xyz[1]+", "+norm_xyz[2]+"}");		norm_xyz[0]+", "+norm_xyz[1]+", "+norm_xyz[2]+"}");

	}		}
	st_planes.add(pd);		st_planes.add(pd); // adding [0] - all supertile tiles, not clustered by disparity value

	// now try for each of the disparity-separated clusters		// now try for each of the disparity-separated clusters (only for multi-peak histograms)

	double [][] mm = maxMinMax[nsTile];		double [][] mm = maxMinMax[nsTile];

	@@ -1392,6 +1378,7 @@ public class SuperTiles{
	stDisparity,		stDisparity,
	stStrength,		stStrength,
	stSels[m],		stSels[m],
			plPreferDisparity,
	0); // debugLevel);		0); // debugLevel);
	if (pd != null) {		if (pd != null) {
	if (dl > 0) {		if (dl > 0) {
	@@ -1426,7 +1413,11 @@ public class SuperTiles{
	targetV, // double targetEigen, // target eigenvalue for primary axis (is disparity-dependent, so is non-constant)		targetV, // double targetEigen, // target eigenvalue for primary axis (is disparity-dependent, so is non-constant)
	max_outliers, // int maxRemoved, // maximal number of tiles to remove (not a constant)		max_outliers, // int maxRemoved, // maximal number of tiles to remove (not a constant)
	plMinPoints, // int minLeft, // minimal number of tiles to keep		plMinPoints, // int minLeft, // minimal number of tiles to keep
			plPreferDisparity,
	dl1); // 0); // debugLevel);		dl1); // 0); // debugLevel);
			if (pd == null) {
			continue;
			}
	if (dl > 0) {		if (dl > 0) {
	if (swc_common > 1.0) {		if (swc_common > 1.0) {
	System.out.println("Removed outliers["+nsTile+"]["+m+"]"+		System.out.println("Removed outliers["+nsTile+"]["+m+"]"+
	@@ -1485,6 +1476,7 @@ public class SuperTiles{

	TilePlanes.PlaneData [][] getNeibPlanes(		TilePlanes.PlaneData [][] getNeibPlanes(
	final int dir, // 0: get from up (N), 1:from NE, ... 7 - from NW		final int dir, // 0: get from up (N), 1:from NE, ... 7 - from NW
			final boolean preferDisparity,
	final boolean dbgMerge, // Combine 'other' plane with current		final boolean dbgMerge, // Combine 'other' plane with current
	final int dbg_X,		final int dbg_X,
	final int dbg_Y		final int dbg_Y
	@@ -1548,12 +1540,14 @@ public class SuperTiles{
	planes[nsTile0][indx], // PlaneData otherPd,		planes[nsTile0][indx], // PlaneData otherPd,
	1.0, // double scale_other,		1.0, // double scale_other,
	true, // boolean ignore_weights,		true, // boolean ignore_weights,
			preferDisparity,
	(nsTile0 == debug_stile)? 1:0); // int debugLevel)		(nsTile0 == debug_stile)? 1:0); // int debugLevel)
	System.out.println("other with other, same weight:");		System.out.println("other with other, same weight:");
	TilePlanes.PlaneData other_other_pd = other_pd.mergePlaneToThis(		TilePlanes.PlaneData other_other_pd = other_pd.mergePlaneToThis(
	other_pd, // PlaneData otherPd,		other_pd, // PlaneData otherPd,
	1.0, // double scale_other,		1.0, // double scale_other,
	true, // boolean ignore_weights,		true, // boolean ignore_weights,
			preferDisparity,
	(nsTile0 == debug_stile)? 1:0); // int debugLevel)		(nsTile0 == debug_stile)? 1:0); // int debugLevel)
	System.out.println("other with this, same weight:");		System.out.println("other with this, same weight:");
	}		}
	@@ -1561,6 +1555,7 @@ public class SuperTiles{
	other_pd, // PlaneData otherPd,		other_pd, // PlaneData otherPd,
	1.0, // double scale_other,		1.0, // double scale_other,
	true, // boolean ignore_weights,		true, // boolean ignore_weights,
			preferDisparity,
	(nsTile0 == debug_stile)? 1:0); // int debugLevel)		(nsTile0 == debug_stile)? 1:0); // int debugLevel)
	if (!(merged_pd.getValue() > best_value)) { // Double.isNaN(best_value) will work too		if (!(merged_pd.getValue() > best_value)) { // Double.isNaN(best_value) will work too
	best_value = merged_pd.getValue();		best_value = merged_pd.getValue();
	@@ -1576,6 +1571,7 @@ public class SuperTiles{
	other_pd, // PlaneData otherPd,		other_pd, // PlaneData otherPd,
	1.0, // double scale_other,		1.0, // double scale_other,
	false, // boolean ignore_weights,		false, // boolean ignore_weights,
			preferDisparity,
	(nsTile0 == debug_stile)? 1:0); // int debugLevel)		(nsTile0 == debug_stile)? 1:0); // int debugLevel)
	neib_planes[nsTile0][np] = merged_pd;		neib_planes[nsTile0][np] = merged_pd;
	} else {		} else {
	@@ -1618,6 +1614,7 @@ public class SuperTiles{
	}		}

	public void matchPlanes(		public void matchPlanes(
			final boolean preferDisparity, // Always start with disparity-most axis (false - lowest eigenvalue)
	final int dbg_X,		final int dbg_X,
	final int dbg_Y)		final int dbg_Y)
	{		{
	@@ -1636,6 +1633,7 @@ public class SuperTiles{

	final Thread[] threads = ImageDtt.newThreadArray(tileProcessor.threadsMax);		final Thread[] threads = ImageDtt.newThreadArray(tileProcessor.threadsMax);
	final AtomicInteger ai = new AtomicInteger(0);		final AtomicInteger ai = new AtomicInteger(0);
			// Select best symmetrical match, consider only N, NE, E, SE - later opposite ones will be copied
	for (int ithread = 0; ithread < threads.length; ithread++) {		for (int ithread = 0; ithread < threads.length; ithread++) {
	threads[ithread] = new Thread() {		threads[ithread] = new Thread() {
	public void run() {		public void run() {
	@@ -1673,6 +1671,7 @@ public class SuperTiles{
	other_plane, // PlaneData otherPd,		other_plane, // PlaneData otherPd,
	1.0, // double scale_other,		1.0, // double scale_other,
	false, // boolean ignore_weights,		false, // boolean ignore_weights,
			preferDisparity,
	dl); // int debugLevel)		dl); // int debugLevel)
	if (merged_pd !=null) { // now always, but may add later		if (merged_pd !=null) { // now always, but may add later
	this_plane.setNeibMatch(dir, np, merged_pd.getValue()); // smallest eigenValue		this_plane.setNeibMatch(dir, np, merged_pd.getValue()); // smallest eigenValue
	@@ -1706,28 +1705,18 @@ public class SuperTiles{
	if ( planes[nsTile0] != null) {		if ( planes[nsTile0] != null) {
	for (int np0 = 0; np0 < planes[nsTile0].length; np0++){ // nu		for (int np0 = 0; np0 < planes[nsTile0].length; np0++){ // nu
	TilePlanes.PlaneData this_plane = planes[nsTile0][np0];		TilePlanes.PlaneData this_plane = planes[nsTile0][np0];
	// this_plane.initMergedValue();
	for (int dir = 4; dir < 8; dir++){ // other half - copy from opposite		for (int dir = 4; dir < 8; dir++){ // other half - copy from opposite
	int stx = stx0 + dirsYX[dir][1];		int stx = stx0 + dirsYX[dir][1];
	int sty = sty0 + dirsYX[dir][0];		int sty = sty0 + dirsYX[dir][0];
	// if ((stx < stilesX) && (sty < stilesY) && (sty > 0)) {
	if ((sty < stilesY) && (sty > 0) && (stx > 0)) {		if ((sty < stilesY) && (sty > 0) && (stx > 0)) {

	int nsTile = sty * stilesX + stx; // from where to get		int nsTile = sty * stilesX + stx; // from where to get
	TilePlanes.PlaneData [] other_planes = planes[nsTile];		TilePlanes.PlaneData [] other_planes = planes[nsTile];
	if (other_planes !=null) {		if (other_planes !=null) {
	this_plane.initMergedValue(dir,other_planes.length); // filled with NaN		this_plane.initMergedValue(dir,other_planes.length); // filled with NaN
	for (int np = 0; np < other_planes.length; np ++){		for (int np = 0; np < other_planes.length; np ++){
	/*
	if ((other_planes[np] != null) && (other_planes[np].getMergedValue(dir-4) != null)) {
	double [] dbg_nm = other_planes[np].getMergedValue(dir-4);
	this_plane.setNeibMatch(dir,np, other_planes[np].getMergedValue(dir-4, np0)); //
	}
	*/
	if (other_planes[np] != null) { // && (other_planes[np].getMergedValue(dir-4) != null)) {		if (other_planes[np] != null) { // && (other_planes[np].getMergedValue(dir-4) != null)) {
	double [] nm = other_planes[np].getMergedValue(dir-4);		double [] nm = other_planes[np].getMergedValue(dir-4);
	if (nm != null) {		if (nm != null) {
	// this_plane.setNeibMatch(dir,np, other_planes[np].getMergedValue(dir-4, np0)); //
	this_plane.setNeibMatch(dir,np, nm[np0]); //		this_plane.setNeibMatch(dir,np, nm[np0]); //
	}		}
	}		}
	@@ -1859,7 +1848,7 @@ public class SuperTiles{
	ImageDtt.startAndJoin(threads);		ImageDtt.startAndJoin(threads);
	}		}
	}		}
	public void fillSquares()		public int fillSquares()
	{		{
	final int tilesX = tileProcessor.getTilesX();		final int tilesX = tileProcessor.getTilesX();
	final int tilesY = tileProcessor.getTilesY();		final int tilesY = tileProcessor.getTilesY();
	@@ -1868,6 +1857,7 @@ public class SuperTiles{
	final int stilesX = (tilesX + superTileSize -1)/superTileSize;		final int stilesX = (tilesX + superTileSize -1)/superTileSize;
	final int stilesY = (tilesY + superTileSize -1)/superTileSize;		final int stilesY = (tilesY + superTileSize -1)/superTileSize;
	final int nStiles = stilesX * stilesY;		final int nStiles = stilesX * stilesY;
			int num_added = 0;
	for (int stY = 0; stY < (stilesY - 1); stY++ ) {		for (int stY = 0; stY < (stilesY - 1); stY++ ) {
	for (int stX = 0; stX < (stilesX - 1); stX++ ) {		for (int stX = 0; stX < (stilesX - 1); stX++ ) {
	int nsTile = stY * stilesX + stX;		int nsTile = stY * stilesX + stX;
	@@ -1891,18 +1881,21 @@ public class SuperTiles{
	if (neibs0[3] < 0) {		if (neibs0[3] < 0) {
	neibs0[3] = neibs1[4];		neibs0[3] = neibs1[4];
	neibs3[7] = np;		neibs3[7] = np;
			num_added++;
	}		}
	if (neibs1[5] < 0){		if (neibs1[5] < 0){
	neibs1[5] = neibs0[4];		neibs1[5] = neibs0[4];
	neibs2[1] = neibs0[2];		neibs2[1] = neibs0[2];
			num_added++;
	}		}
	}		}
	}		}
	}		}
	}		}
			return num_added;
	}		}

	public void cutCorners()		public int cutCorners()
	{		{
	final int tilesX = tileProcessor.getTilesX();		final int tilesX = tileProcessor.getTilesX();
	final int tilesY = tileProcessor.getTilesY();		final int tilesY = tileProcessor.getTilesY();
	@@ -1910,7 +1903,8 @@ public class SuperTiles{
	// final int tileSize = tileProcessor.getTileSize();		// final int tileSize = tileProcessor.getTileSize();
	final int stilesX = (tilesX + superTileSize -1)/superTileSize;		final int stilesX = (tilesX + superTileSize -1)/superTileSize;
	final int stilesY = (tilesY + superTileSize -1)/superTileSize;		final int stilesY = (tilesY + superTileSize -1)/superTileSize;
	final int nStiles = stilesX * stilesY;		// final int nStiles = stilesX * stilesY;
			int num_added = 0;
	for (int stY = 0; stY < (stilesY - 1); stY++ ) {		for (int stY = 0; stY < (stilesY - 1); stY++ ) {
	for (int stX = 0; stX < (stilesX - 1); stX++ ) {		for (int stX = 0; stX < (stilesX - 1); stX++ ) {
	int nsTile = stY * stilesX + stX;		int nsTile = stY * stilesX + stX;
	@@ -1931,6 +1925,7 @@ public class SuperTiles{
	neibs0[4] = neibs1[5];		neibs0[4] = neibs1[5];
	int [] neibs2 = planes4[2][neibs1[5]].getNeibBest();		int [] neibs2 = planes4[2][neibs1[5]].getNeibBest();
	neibs2[0] = np; //?		neibs2[0] = np; //?
			num_added++;
	}		}
	}		}
	}		}
	@@ -1942,6 +1937,7 @@ public class SuperTiles{
	neibs0[2] = neibs2[1];		neibs0[2] = neibs2[1];
	int [] neibs1 = planes4[1][neibs2[1]].getNeibBest();		int [] neibs1 = planes4[1][neibs2[1]].getNeibBest();
	neibs1[6] = np;		neibs1[6] = np;
			num_added++;
	}		}
	}		}
	}		}
	@@ -1951,6 +1947,7 @@ public class SuperTiles{
	if (neibs1[4] < 0) {		if (neibs1[4] < 0) {
	neibs1[4] = neibs0[3];		neibs1[4] = neibs0[3];
	neibs3[0] = neibs0[2]; //?		neibs3[0] = neibs0[2]; //?
			num_added++;
	}		}
	}		}
	if ((neibs0[3] >= 0) && (neibs0[4] >= 0)){		if ((neibs0[3] >= 0) && (neibs0[4] >= 0)){
	@@ -1959,6 +1956,7 @@ public class SuperTiles{
	if (neibs2[2] < 0) {		if (neibs2[2] < 0) {
	neibs2[2] = neibs0[3];		neibs2[2] = neibs0[3];
	neibs3[6] = neibs0[4];		neibs3[6] = neibs0[4];
			num_added++;
	}		}
	}		}
	}		}
	@@ -1975,6 +1973,7 @@ public class SuperTiles{
	if (neibs0[2] < 0) {		if (neibs0[2] < 0) {
	neibs0[2] = neibs3[0];		neibs0[2] = neibs3[0];
	neibs1[6] = neibs3[7];		neibs1[6] = neibs3[7];
			num_added++;
	}		}
	}		}

	@@ -1985,6 +1984,7 @@ public class SuperTiles{
	if (neibs0[4] < 0) {		if (neibs0[4] < 0) {
	neibs0[4] = neibs3[6];		neibs0[4] = neibs3[6];
	neibs2[0] = neibs3[7]; //?		neibs2[0] = neibs3[7]; //?
			num_added++;
	}		}
	}		}

	@@ -1996,6 +1996,7 @@ public class SuperTiles{
	int [] neibs2 = planes4[2][neibs0[4]].getNeibBest();		int [] neibs2 = planes4[2][neibs0[4]].getNeibBest();
	neibs3[6] = neibs0[4];		neibs3[6] = neibs0[4];
	neibs2[2] = np; //?		neibs2[2] = np; //?
			num_added++;
	}		}
	}		}

	@@ -2006,6 +2007,7 @@ public class SuperTiles{
	int [] neibs1 = planes4[1][neibs2[1]].getNeibBest();		int [] neibs1 = planes4[1][neibs2[1]].getNeibBest();
	neibs3[0] = neibs2[1]; //?		neibs3[0] = neibs2[1]; //?
	neibs1[4] = np;		neibs1[4] = np;
			num_added++;
	}		}
	}		}
	}		}
	@@ -2013,6 +2015,8 @@ public class SuperTiles{
	}		}
	}		}
	}		}
			return num_added;

	}		}

	/**		/**
	@@ -2027,6 +2031,7 @@ public class SuperTiles{
	*/		*/
	public void selectNeighborPlanesMutual(		public void selectNeighborPlanesMutual(
	final double rquality,		final double rquality,
			final double weakWorsening,
	final double dispNorm,		final double dispNorm,
	final double maxEigen, // maximal eigenvalue of planes to consider		final double maxEigen, // maximal eigenvalue of planes to consider
	final double minWeight, // minimal pain weight to consider		final double minWeight, // minimal pain weight to consider
	@@ -2130,8 +2135,9 @@ public class SuperTiles{
	merge_ev[np], // double L,		merge_ev[np], // double L,
	w1, // double w1,		w1, // double w1,
	w2); // double w2)		w2); // double w2)
	// if (this_rq <= rquality) { // compare with the threshold before applying strengths		double this_rq_norm = this_rq;
	if ((w1 + w2) * this_rq <= rquality) { // forgive more for weak planes		if ((w1 + w2) < weakWorsening) this_rq_norm *= (w1 + w2) / weakWorsening; // forgive more for weak planes
			if (this_rq_norm <= rquality) {
	this_rq /= (w1 + w2); // for comparision reduce this value for stronger planes		this_rq /= (w1 + w2); // for comparision reduce this value for stronger planes
	if (Double.isNaN(best_rqual) \|\| (this_rq < best_rqual)){ // OK if Double.isNaN(this_rq[np])		if (Double.isNaN(best_rqual) \|\| (this_rq < best_rqual)){ // OK if Double.isNaN(this_rq[np])
	best_rqual = this_rq;		best_rqual = this_rq;
	@@ -2504,6 +2510,7 @@ public class SuperTiles{
	final double meas_pull,// relative pull of the original (measured) plane with respect to the average of the neighbors		final double meas_pull,// relative pull of the original (measured) plane with respect to the average of the neighbors
	final int num_passes,		final int num_passes,
	final double maxDiff, // maximal change in any of the disparity values		final double maxDiff, // maximal change in any of the disparity values
			final boolean preferDisparity, // Always start with disparity-most axis (false - lowest eigenvalue)
	final int debugLevel,		final int debugLevel,
	final int dbg_X,		final int dbg_X,
	final int dbg_Y)		final int dbg_Y)
	@@ -2517,6 +2524,7 @@ public class SuperTiles{
	this.planes, // final TilePlanes.PlaneData[][] measured_planes,		this.planes, // final TilePlanes.PlaneData[][] measured_planes,
	this.planes_mod, // final TilePlanes.PlaneData[][] mod_planes,		this.planes_mod, // final TilePlanes.PlaneData[][] mod_planes,
	true, // final boolean calc_diff,		true, // final boolean calc_diff,
			preferDisparity,
	(pass < 10)? debugLevel: 0,		(pass < 10)? debugLevel: 0,
	dbg_X,		dbg_X,
	dbg_Y);		dbg_Y);
	@@ -2539,6 +2547,7 @@ public class SuperTiles{
	final TilePlanes.PlaneData[][] measured_planes,		final TilePlanes.PlaneData[][] measured_planes,
	final TilePlanes.PlaneData[][] mod_planes,		final TilePlanes.PlaneData[][] mod_planes,
	final boolean calc_diff,		final boolean calc_diff,
			final boolean preferDisparity, // Always start with disparity-most axis (false - lowest eigenvalue)
	final int debugLevel,		final int debugLevel,
	final int dbg_X,		final int dbg_X,
	final int dbg_Y)		final int dbg_Y)
	@@ -2600,6 +2609,7 @@ public class SuperTiles{
	other_plane, // PlaneData otherPd,		other_plane, // PlaneData otherPd,
	1.0, // double scale_other,		1.0, // double scale_other,
	false, // boolean ignore_weights,		false, // boolean ignore_weights,
			preferDisparity,
	dl); // int debugLevel)		dl); // int debugLevel)
	} else {		} else {
	this_new_plane = other_plane;		this_new_plane = other_plane;
	@@ -2619,6 +2629,7 @@ public class SuperTiles{
	measured_planes[nsTile0][np0], // PlaneData otherPd,		measured_planes[nsTile0][np0], // PlaneData otherPd,
	meas_pull, // double scale_other,		meas_pull, // double scale_other,
	false, // boolean ignore_weights,		false, // boolean ignore_weights,
			preferDisparity,
	dl); // int debugLevel)		dl); // int debugLevel)
	} else {		} else {
	this_new_plane = measured_planes[nsTile0][np0].clone();		this_new_plane = measured_planes[nsTile0][np0].clone();

Original line number	Original line	Diff line number	Diff line
	@@ -2142,6 +2142,7 @@ public class EyesisCorrectionParameters {
	public double grow_disp_step = 6.0; // Increase disparity (from maximal tried) if nothing found in that tile // TODO: handle enclosed dips?		public double grow_disp_step = 6.0; // Increase disparity (from maximal tried) if nothing found in that tile // TODO: handle enclosed dips?
	public double grow_min_diff = 0.5; // Grow more only if at least one channel has higher variance from others for the tile		public double grow_min_diff = 0.5; // Grow more only if at least one channel has higher variance from others for the tile

			public boolean plPreferDisparity = false;// Always start with disparity-most axis (false - lowest eigenvalue)
	public double plDispNorm = 3.0; // Normalize disparities to the average if above (now only for eigenvalue comparison)		public double plDispNorm = 3.0; // Normalize disparities to the average if above (now only for eigenvalue comparison)
	public int plMinPoints = 5; // Minimal number of points for plane detection		public int plMinPoints = 5; // Minimal number of points for plane detection
	public double plTargetEigen = 0.1; // Remove outliers until main axis eigenvalue (possibly scaled by plDispNorm) gets below		public double plTargetEigen = 0.1; // Remove outliers until main axis eigenvalue (possibly scaled by plDispNorm) gets below
	@@ -2150,7 +2151,8 @@ public class EyesisCorrectionParameters {
	public double plMinStrength = 0.1; // Minimal total strength of a plane		public double plMinStrength = 0.1; // Minimal total strength of a plane
	public double plMaxEigen = 0.3; // Maximal eigenvalue of a plane		public double plMaxEigen = 0.3; // Maximal eigenvalue of a plane
	public boolean plDbgMerge = true; // Combine 'other' plane with current		public boolean plDbgMerge = true; // Combine 'other' plane with current
	public double plWorstWorsening = 1.0; // Worst case worsening after merge		public double plWorstWorsening = 3.0; // Worst case worsening after merge
			public double plWeakWorsening = 1.0; // Relax merge requirements for weaker planes
	public boolean plMutualOnly = true; // keep only mutual links, remove weakest if conflict		public boolean plMutualOnly = true; // keep only mutual links, remove weakest if conflict
	public boolean plFillSquares = true; // Add diagonals to full squares		public boolean plFillSquares = true; // Add diagonals to full squares
	public boolean plCutCorners = true; // Add ortho to 45-degree corners		public boolean plCutCorners = true; // Add ortho to 45-degree corners
	@@ -2406,6 +2408,7 @@ public class EyesisCorrectionParameters {
	properties.setProperty(prefix+"grow_disp_step", this.grow_disp_step +"");		properties.setProperty(prefix+"grow_disp_step", this.grow_disp_step +"");
	properties.setProperty(prefix+"grow_min_diff", this.grow_min_diff +"");		properties.setProperty(prefix+"grow_min_diff", this.grow_min_diff +"");

			properties.setProperty(prefix+"plPreferDisparity",this.plPreferDisparity+"");
	properties.setProperty(prefix+"plDispNorm", this.plDispNorm +"");		properties.setProperty(prefix+"plDispNorm", this.plDispNorm +"");
	properties.setProperty(prefix+"plMinPoints", this.plMinPoints+"");		properties.setProperty(prefix+"plMinPoints", this.plMinPoints+"");
	properties.setProperty(prefix+"plTargetEigen", this.plTargetEigen +"");		properties.setProperty(prefix+"plTargetEigen", this.plTargetEigen +"");
	@@ -2415,6 +2418,7 @@ public class EyesisCorrectionParameters {
	properties.setProperty(prefix+"plMaxEigen", this.plMaxEigen +"");		properties.setProperty(prefix+"plMaxEigen", this.plMaxEigen +"");
	properties.setProperty(prefix+"plDbgMerge", this.plDbgMerge+"");		properties.setProperty(prefix+"plDbgMerge", this.plDbgMerge+"");
	properties.setProperty(prefix+"plWorstWorsening", this.plWorstWorsening +"");		properties.setProperty(prefix+"plWorstWorsening", this.plWorstWorsening +"");
			properties.setProperty(prefix+"plWeakWorsening", this.plWeakWorsening +"");
	properties.setProperty(prefix+"plMutualOnly", this.plMutualOnly+"");		properties.setProperty(prefix+"plMutualOnly", this.plMutualOnly+"");

	properties.setProperty(prefix+"plFillSquares", this.plFillSquares+"");		properties.setProperty(prefix+"plFillSquares", this.plFillSquares+"");
	@@ -2657,6 +2661,7 @@ public class EyesisCorrectionParameters {
	if (properties.getProperty(prefix+"grow_disp_step")!=null) this.grow_disp_step=Double.parseDouble(properties.getProperty(prefix+"grow_disp_step"));		if (properties.getProperty(prefix+"grow_disp_step")!=null) this.grow_disp_step=Double.parseDouble(properties.getProperty(prefix+"grow_disp_step"));
	if (properties.getProperty(prefix+"grow_min_diff")!=null) this.grow_min_diff=Double.parseDouble(properties.getProperty(prefix+"grow_min_diff"));		if (properties.getProperty(prefix+"grow_min_diff")!=null) this.grow_min_diff=Double.parseDouble(properties.getProperty(prefix+"grow_min_diff"));

			if (properties.getProperty(prefix+"plPreferDisparity")!=null) this.plPreferDisparity=Boolean.parseBoolean(properties.getProperty(prefix+"plPreferDisparity"));
	if (properties.getProperty(prefix+"plDispNorm")!=null) this.plDispNorm=Double.parseDouble(properties.getProperty(prefix+"plDispNorm"));		if (properties.getProperty(prefix+"plDispNorm")!=null) this.plDispNorm=Double.parseDouble(properties.getProperty(prefix+"plDispNorm"));
	if (properties.getProperty(prefix+"plMinPoints")!=null) this.plMinPoints=Integer.parseInt(properties.getProperty(prefix+"plMinPoints"));		if (properties.getProperty(prefix+"plMinPoints")!=null) this.plMinPoints=Integer.parseInt(properties.getProperty(prefix+"plMinPoints"));

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