improving/fixing bugs in the sensors calibration. (5de61cce) · Commits · Elphel / imagej-elphel

src/main/java/com/elphel/imagej/calibration/Aberration_Calibration.java

+144 −0

Original line number	Original line	Diff line number	Diff line
	@@ -515,6 +515,7 @@ public static MatchSimulatedPattern.DistortionParameters DISTORTION =new MatchSi
	0.3, // public double weightBad = 0.3; // reduce contrast of bad nodes		0.3, // public double weightBad = 0.3; // reduce contrast of bad nodes
	0.05, // public double weightWorst = 0.05; // reduce contrast of bad, local worst nodes		0.05, // public double weightWorst = 0.05; // reduce contrast of bad, local worst nodes
	0.1, // double badNodeThreshold=0.1; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		0.1, // double badNodeThreshold=0.1; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			0.2, // public double badNodeThresholdLWIR=0.2; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
	1, // int maxBadNeighb; // maximal number of bad nodes around the corrected one to fix		1, // int maxBadNeighb; // maximal number of bad nodes around the corrected one to fix
	10, // int minimalValidNodes		10, // int minimalValidNodes
	1, // int weightMultiImageMode=1; // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)		1, // int weightMultiImageMode=1; // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)
	@@ -1037,6 +1038,7 @@ if (MORE_BUTTONS) {
	addButton("Import Subsystem", panelLWIR,color_configure);		addButton("Import Subsystem", panelLWIR,color_configure);
	addButton("Select LWIR grids", panelLWIR,color_configure);		addButton("Select LWIR grids", panelLWIR,color_configure);
	addButton("Grid offset", panelLWIR,color_process);		addButton("Grid offset", panelLWIR,color_process);
			addButton("EO Offsets", panelLWIR,color_process);
	addButton("LWIR to EO", panelLWIR,color_process);		addButton("LWIR to EO", panelLWIR,color_process);
	addButton("Manual hint", panelLWIR,color_configure);		addButton("Manual hint", panelLWIR,color_configure);

	@@ -9420,6 +9422,13 @@ if (MORE_BUTTONS) {
	offsetGrids(0, 0, null, null);		offsetGrids(0, 0, null, null);
	return;		return;
	}		}
			/* ======================================================================== */
			if (label.equals("EO Offsets")) {
			DEBUG_LEVEL=MASTER_DEBUG_LEVEL;
			EOoffsets();
			return;
			}

	/* ======================================================================== */		/* ======================================================================== */
	if (label.equals("LWIR to EO")) {		if (label.equals("LWIR to EO")) {
	DEBUG_LEVEL=MASTER_DEBUG_LEVEL;		DEBUG_LEVEL=MASTER_DEBUG_LEVEL;
	@@ -9435,6 +9444,141 @@ if (MORE_BUTTONS) {
	}		}

	/* ===== Other methods ==================================================== */		/* ===== Other methods ==================================================== */
			//();

			public boolean EOoffsets() {
			if (LENS_DISTORTIONS == null) {
			System.out.println("LENS_DISTORTIONS is null");
			return false;
			}
			if (PATTERN_PARAMETERS == null) {
			System.out.println("PATTERN_PARAMETERS is null");
			return false;
			}
			DistortionCalibrationData dcd = LENS_DISTORTIONS.getDistortionCalibrationData();
			if (dcd == null) {
			dcd = DISTORTION_CALIBRATION_DATA;
			}
			if (dcd == null) {
			System.out.println("dcd is null");
			return false;
			}

			int min_set = 0;
			int max_set = dcd.getNumSets()-1;
			double maximalRMS = 1.0;
			double maximalGridErr = 0.2;
			boolean adjustAttitude = true;
			// int extra_search = 2;
			// double sigma = 5;


			GenericDialog gd = new GenericDialog("Initial alignment of the secondary camera to the reference one");
			// gd.addMessage("This command used Fitting Strategy[last] that should be set with all parameters but\n"+
			// "GXYZ0 and GXYZ1 are set to 'fixed', and GXYZ0 and GXYZ1 are set to 'individual'.\n"+
			// "Each selected set should already have GXYZ set correctly (e.g. by reference cameras)");
			gd.addMessage("This command uses Fitting Strategy[last] and set parameters but\n"+
			"GXYZ0 and GXYZ1 to 'individual', all others - to 'fixed'.\n"+
			"Each selected set should already have GXYZ set correctly (e.g. by reference cameras)");
			gd.addNumericField("Image set start", min_set, 0);
			gd.addNumericField("Image set last", max_set, 0);
			gd.addNumericField("Maximal RMS to accept", maximalRMS, 3 ,7, "");
			gd.addNumericField("Maximal grid errot to accept", maximalGridErr, 3 ,7, "");
			gd.addCheckbox("Adjust set attitude after grid offsets", adjustAttitude);

			// gd.addNumericField("Extra search for the non-LMA method", extra_search, 0);
			// gd.addNumericField("Sigma for the non-LMA method", sigma, 3 ,7, "");
			gd.showDialog();
			if (gd.wasCanceled()) return false;
			min_set = (int) gd.getNextNumber();
			max_set = (int) gd.getNextNumber();
			maximalRMS = gd.getNextNumber();
			maximalGridErr = gd.getNextNumber();
			// extra_search = (int) gd.getNextNumber();
			// sigma = gd.getNextNumber();
			adjustAttitude = gd.getNextBoolean();
			if (!dcd.hasSmallSensors()) {
			String msg="This system does not have any LWIR or other dependent sub-cameras";
			IJ.showMessage("Error",msg);
			return false;
			}

			for (int num_set = min_set; num_set <=max_set; num_set++) if
			((dcd.gIS[num_set] != null) && (dcd.gIS[num_set].imageSet != null)) {
			ArrayList<Integer> num_imgs_list = new ArrayList<Integer>();
			for (int nc = 0; nc < dcd.getNumChannels(); nc++) {
			if (dcd.gIS[num_set].imageSet[nc]!= null) {
			int num_img = dcd.gIS[num_set].imageSet[nc].imgNumber;
			if (dcd.isSmallSensor(num_img)) {
			continue;
			}
			double [] stats = new double [3];
			int [] uvr = LENS_DISTORTIONS.findImageGridOffset(
			num_img, // image num
			-1, // use last series int ser_num, // number of series to reprogram
			true, // boolean adjust_attitude, // true for eo, false for lwir (uses exact attitude from eo)
			true, // boolean even, For first time - use parameter and parity of uv_rot
			PATTERN_PARAMETERS,
			stats); // rms, dU, dV
			if (uvr == null) {
			if (DEBUG_LEVEL > 0) {
			System.out.println("LMA failed for set = "+ num_set +", channel = "+nc);
			}
			continue;
			}
			if (DEBUG_LEVEL > 0) {
			System.out.println(num_img+ "("+num_set+"."+nc+"): uv_shift = "+uvr[0]+":"+uvr[1]);
			System.out.println(num_img+ "("+num_set+"."+nc+"): errors: rms= "+stats[0]+", dU="+stats[1]+", dV="+stats[2]);
			}
			if ((maximalRMS > 0.0) && (stats[0] >maximalRMS)) {
			if (DEBUG_LEVEL > 0) {
			System.out.println("LMA RMS for set = "+ num_set +", channel = "+nc+" is too high: "+stats[0]+" > "+maximalRMS);
			}
			continue;
			}
			double grid_err =Math.max(Math.abs(stats[1]), Math.abs(stats[2]));
			if ((maximalGridErr > 0.0) && (grid_err > maximalGridErr)) {
			if (DEBUG_LEVEL > 0) {
			System.out.println("Adjusted grid error for set = "+ num_set +", channel = "+nc+" is too high: "+
			grid_err+" > "+maximalGridErr);
			}
			continue;
			}
			num_imgs_list.add(num_img);
			if ((uvr[0] == 0) \|\| (uvr[1] == 0)) {
			if (DEBUG_LEVEL > 0) {
			System.out.println("Grid alignment for set = "+ num_set +", channel = "+nc+" was correct, nothing to do");
			}
			continue;
			}

			int [] uv_shift_rot = {uvr[0],uvr[1],0};
			// int [] new_uv_shift_rots =
			dcd.offsetGrid(
			num_img, // int img_num,
			uv_shift_rot,
			PATTERN_PARAMETERS);
			if (DEBUG_LEVEL > 0) {
			System.out.println("Grid for set = "+ num_set +", channel = "+nc+" adjusted by "+uvr[0]+":"+uvr[1]);
			}
			// num_imgs_list.add(num_img);
			}
			}
			if (adjustAttitude && !num_imgs_list.isEmpty()) {
			int [] num_imgs = new int[num_imgs_list.size()];
			for (int i = 0; i < num_imgs.length; i++) {
			num_imgs[i] = num_imgs_list.get(i);
			}
			LENS_DISTORTIONS.adjustAttitudeAfterOffset(
			num_imgs,
			-1, // number of series to reprogram
			PATTERN_PARAMETERS);
			}

			}
			return true;
			}


	public boolean lwirToEo() {		public boolean lwirToEo() {
	if (LENS_DISTORTIONS == null) {		if (LENS_DISTORTIONS == null) {

src/main/java/com/elphel/imagej/calibration/DistortionCalibrationData.java

+27 −11

Original line number	Original line	Diff line number	Diff line
	@@ -71,6 +71,8 @@ import ij.text.TextWindow;
	public static final int INDEX_B = 7;		public static final int INDEX_B = 7;
	public static final double SMALL_FRACTION = 0.8; // consider sensor to be a "small" if average grid period < this fraction of the large		public static final double SMALL_FRACTION = 0.8; // consider sensor to be a "small" if average grid period < this fraction of the large

			public static final int MAX_LWIR_WIDTH = 1023; // Consider smaller sensors to be low-res

	Goniometer.GoniometerParameters goniometerParameters = null;		Goniometer.GoniometerParameters goniometerParameters = null;
	public String pathName=null;		public String pathName=null;
	public EyesisCameraParameters eyesisCameraParameters; // has "cartesian"		public EyesisCameraParameters eyesisCameraParameters; // has "cartesian"
	@@ -967,7 +969,6 @@ import ij.text.TextWindow;
	}		}
	this.goniometerParameters = goniometerParameters;		this.goniometerParameters = goniometerParameters;
	boolean ignore_LWIR_pointers = true; // skip LWIR absolute marks, use them later		boolean ignore_LWIR_pointers = true; // skip LWIR absolute marks, use them later
	int max_lwir_width = 1023; // use LWIR class
	setupIndices();		setupIndices();
	this.eyesisCameraParameters=eyesisCameraParameters;		this.eyesisCameraParameters=eyesisCameraParameters;
	int numSubCameras=(eyesisCameraParameters==null)?1:eyesisCameraParameters.eyesisSubCameras[0].length;		int numSubCameras=(eyesisCameraParameters==null)?1:eyesisCameraParameters.eyesisSubCameras[0].length;
	@@ -1034,7 +1035,7 @@ import ij.text.TextWindow;
	this.gIP[numFile].setNumber = nis;		this.gIP[numFile].setNumber = nis;
	this.gIP[numFile].gridImageSet = this.gIS[nis];		this.gIP[numFile].gridImageSet = this.gIS[nis];
	this.gIS[nis].imageSet[nc]=this.gIP[numFile];		this.gIS[nis].imageSet[nc]=this.gIP[numFile];
			boolean is_small = getImagePlusProperty(imp_grid,"WOI_WIDTH",0) <= MAX_LWIR_WIDTH;
	//numFile		//numFile
	if (first_in_set \|\| read_grids) {		if (first_in_set \|\| read_grids) {
	if (read_grids) {		if (read_grids) {
	@@ -1064,10 +1065,14 @@ import ij.text.TextWindow;
	this.gIS[nis].motors= this.gIP[numFile].motors.clone();		this.gIS[nis].motors= this.gIP[numFile].motors.clone();
	this.gIP[numFile].matchedPointers = getUsedPonters(imp_grid);		this.gIP[numFile].matchedPointers = getUsedPonters(imp_grid);
	if (this.gIP[numFile].matchedPointers > 0) {		if (this.gIP[numFile].matchedPointers > 0) {
			System.out.print("<"+(this.gIP[numFile].matchedPointers));
	// Not using LWIR pointers here!		// Not using LWIR pointers here!
	if (!ignore_LWIR_pointers \|\| (getImagePlusProperty(imp_grid,"WOI_TOP",0) > max_lwir_width)) {		// if (!ignore_LWIR_pointers \|\| (getImagePlusProperty(imp_grid,"WOI_TOP",0) > MAX_LWIR_WIDTH)) {
			if (!ignore_LWIR_pointers \|\| !is_small) {
	with_pointers = numFile;		with_pointers = numFile;
			System.out.print("\|"+numFile);
	}		}
			System.out.print(">");
	}		}
	double [] saturations=new double [4];		double [] saturations=new double [4];
	for (int i=0;i<saturations.length;i++) {		for (int i=0;i<saturations.length;i++) {
	@@ -1108,7 +1113,8 @@ import ij.text.TextWindow;


	int [] numBadNodes = new int [2];		int [] numBadNodes = new int [2];
	if (this.eyesisCameraParameters.badNodeThreshold>0.0){		double badNodeThreshold = is_small? this.eyesisCameraParameters.badNodeThresholdLWIR : this.eyesisCameraParameters.badNodeThreshold;
			if (badNodeThreshold > 0.0){
	boolean thisDebug =false;		boolean thisDebug =false;
	// thisDebug\|= (fileNumber== 720); // chn 25		// thisDebug\|= (fileNumber== 720); // chn 25
	numBadNodes=fixBadGridNodes(		numBadNodes=fixBadGridNodes(
	@@ -1118,7 +1124,7 @@ import ij.text.TextWindow;
	this.eyesisCameraParameters.removeWorst,		this.eyesisCameraParameters.removeWorst,
	this.eyesisCameraParameters.weightBad,		this.eyesisCameraParameters.weightBad,
	this.eyesisCameraParameters.weightWorst,		this.eyesisCameraParameters.weightWorst,
	this.eyesisCameraParameters.badNodeThreshold,		badNodeThreshold,
	this.eyesisCameraParameters.maxBadNeighb,		this.eyesisCameraParameters.maxBadNeighb,
	this.debugLevel+(thisDebug?3:0),		this.debugLevel+(thisDebug?3:0),
	thisDebug?("fixBad-"+numFile):null		thisDebug?("fixBad-"+numFile):null
	@@ -1241,7 +1247,7 @@ import ij.text.TextWindow;
	5.0, // 2.0, // sigma		5.0, // 2.0, // sigma
	sensor_wh,		sensor_wh,
	false); // true);		false); // true);
	System.out.print(" {"+uv_shift_rot[0]+":"+uv_shift_rot[1]+"->");		System.out.print(" {{"+uv_shift_rot[0]+":"+uv_shift_rot[1]+"->");
	int [] combinedUVShiftRot=MatchSimulatedPattern.combineUVShiftRot(		int [] combinedUVShiftRot=MatchSimulatedPattern.combineUVShiftRot(
	this.gIS[nis].imageSet[base_channel].getUVShiftRot(),		this.gIS[nis].imageSet[base_channel].getUVShiftRot(),
	uv_shift_rot);		uv_shift_rot);
	@@ -3880,6 +3886,7 @@ import ij.text.TextWindow;
	this.gIP[fileNumber].gridImage = imp_grid;		this.gIP[fileNumber].gridImage = imp_grid;
	}		}
	}		}
			boolean is_small = getImagePlusProperty(imp_grid,"WOI_WIDTH",0) <= MAX_LWIR_WIDTH;
	this.gIP[fileNumber].woi = new Rectangle(		this.gIP[fileNumber].woi = new Rectangle(
	getImagePlusProperty(imp_grid,"WOI_LEFT",0),		getImagePlusProperty(imp_grid,"WOI_LEFT",0),
	getImagePlusProperty(imp_grid,"WOI_TOP",0),		getImagePlusProperty(imp_grid,"WOI_TOP",0),
	@@ -3922,8 +3929,10 @@ import ij.text.TextWindow;
	woi_compensated = true;		woi_compensated = true;

	}		}
			double badNodeThreshold = is_small? this.eyesisCameraParameters.badNodeThresholdLWIR : this.eyesisCameraParameters.badNodeThreshold;
			// TODO: maybe adjust threshold to grid period, not the sensor type?

	if (this.eyesisCameraParameters.badNodeThreshold>0.0){		if (badNodeThreshold>0.0){
	boolean thisDebug =false;		boolean thisDebug =false;
	// thisDebug\|= (fileNumber== 720); // chn 25		// thisDebug\|= (fileNumber== 720); // chn 25
	int [] numBadNodes=fixBadGridNodes(		int [] numBadNodes=fixBadGridNodes(
	@@ -3933,7 +3942,7 @@ import ij.text.TextWindow;
	this.eyesisCameraParameters.removeWorst,		this.eyesisCameraParameters.removeWorst,
	this.eyesisCameraParameters.weightBad,		this.eyesisCameraParameters.weightBad,
	this.eyesisCameraParameters.weightWorst,		this.eyesisCameraParameters.weightWorst,
	this.eyesisCameraParameters.badNodeThreshold,		badNodeThreshold,
	this.eyesisCameraParameters.maxBadNeighb,		this.eyesisCameraParameters.maxBadNeighb,
	this.debugLevel+(thisDebug?3:0),		this.debugLevel+(thisDebug?3:0),
	thisDebug?("fixBad-"+fileNumber):null		thisDebug?("fixBad-"+fileNumber):null
	@@ -3941,11 +3950,11 @@ import ij.text.TextWindow;
	if (this.debugLevel>-1) {		if (this.debugLevel>-1) {
	if ((numBadNodes[0] + numBadNodes [1])>0) {		if ((numBadNodes[0] + numBadNodes [1])>0) {
	if (this.eyesisCameraParameters.removeWorst) {		if (this.eyesisCameraParameters.removeWorst) {
	System.out.print(" -- removed "+numBadNodes[0]+"("+numBadNodes[1]+") locally worst grid nodes,");		System.out.print(" --- removed "+numBadNodes[0]+"("+numBadNodes[1]+") locally worst grid nodes,");
	} else if (this.eyesisCameraParameters.replaceBad){		} else if (this.eyesisCameraParameters.replaceBad){
	System.out.print(" -- replaced "+numBadNodes[0]+"("+numBadNodes[1]+") bad grid nodes,");		System.out.print(" --- replaced "+numBadNodes[0]+"("+numBadNodes[1]+") bad grid nodes,");
	} else {		} else {
	System.out.print(" -- scaled "+numBadNodes[0]+"("+numBadNodes[1]+") bad grid nodes,");		System.out.print(" --- scaled "+numBadNodes[0]+"("+numBadNodes[1]+") bad grid nodes,");
	}		}
	}		}

	@@ -5119,6 +5128,13 @@ import ij.text.TextWindow;
	double sigma=sigmaUV;		double sigma=sigmaUV;
	if(sigma<0) sigma*=-rAverage;		if(sigma<0) sigma*=-rAverage;
	gb.blurDouble(this.sensorMasks[chNum], dWidth, dHeight, sigma/decimate, sigma/decimate, 0.01);		gb.blurDouble(this.sensorMasks[chNum], dWidth, dHeight, sigma/decimate, sigma/decimate, 0.01);
			if (this.debugLevel >1) {
			(new ShowDoubleFloatArrays()).showArrays(
			this.sensorMasks[chNum],
			dWidth,
			dHeight,
			"SensorMask"+chNum);
			}
	}		}
	return this.sensorMasks;		return this.sensorMasks;
	}		}

src/main/java/com/elphel/imagej/calibration/Distortions.java

+20 −2

Original line number	Original line	Diff line number	Diff line
	@@ -8130,6 +8130,7 @@ List calibration
	if (!LMA_OK) {		if (!LMA_OK) {
	return null; // LMA did not converge		return null; // LMA did not converge
	}		}

	// DistortionCalibrationData dcd = this.fittingStrategy.distortionCalibrationData;		// DistortionCalibrationData dcd = this.fittingStrategy.distortionCalibrationData;
	// find indices of GXYZ0 and GXYZ1 in the vector		// find indices of GXYZ0 and GXYZ1 in the vector
	int index_GXYZ0 = this.fittingStrategy.reverseParameterMap[num_img][par_index_GXYZ0];		int index_GXYZ0 = this.fittingStrategy.reverseParameterMap[num_img][par_index_GXYZ0];
	@@ -8169,11 +8170,26 @@ List calibration
	int num_img,		int num_img,
	int ser_num, // number of series to reprogram		int ser_num, // number of series to reprogram
	PatternParameters patternParameters) {		PatternParameters patternParameters) {
			int [] num_imgs = {num_img};
			return adjustAttitudeAfterOffset(
			num_imgs,
			ser_num, // number of series to reprogram
			patternParameters);
			}

			public boolean adjustAttitudeAfterOffset(
			int [] num_imgs,
			int ser_num, // number of series to reprogram
			PatternParameters patternParameters) {
	if (ser_num < 0) {		if (ser_num < 0) {
	ser_num = fittingStrategy.parameterMode.length + ser_num; // use from the last one		ser_num = fittingStrategy.parameterMode.length + ser_num; // use from the last one
	}		}
	if (this.debugLevel > 0) {		if (this.debugLevel > 0) {
	System.out.println("Will use/modify fitting series "+ser_num+" for to adjust az, tilt of image "+num_img);		System.out.print("Will use/modify fitting series "+ser_num+" for to adjust az, tilt of images: ");
			for (int num_img: num_imgs) {
			System.out.print(" "+num_img);
			}
			System.out.println();
	System.out.println("Will adjust goniometerHorizontal, and goniometerAxial");		System.out.println("Will adjust goniometerHorizontal, and goniometerAxial");
	}		}
	int was_seriesNumber = seriesNumber;		int was_seriesNumber = seriesNumber;
	@@ -8188,7 +8204,9 @@ List calibration
	fittingStrategy.parameterMode[ser_num][par_index_goniometerAxial] = FittingStrategy.modeIndividual; // 3		fittingStrategy.parameterMode[ser_num][par_index_goniometerAxial] = FittingStrategy.modeIndividual; // 3
	boolean [] selection = fittingStrategy.selectAllImages(ser_num); // enable all images in series 0		boolean [] selection = fittingStrategy.selectAllImages(ser_num); // enable all images in series 0
	for (int i=0;i<selection.length;i++) selection[i]=false;		for (int i=0;i<selection.length;i++) selection[i]=false;
			for (int num_img:num_imgs) {
	selection[num_img]=true;		selection[num_img]=true;
			}
	fittingStrategy.setImageSelection(ser_num,selection);		fittingStrategy.setImageSelection(ser_num,selection);
	seriesNumber= ser_num; // start from 0;		seriesNumber= ser_num; // start from 0;
	initFittingSeries(false, filterForAll,ser_num); // will set this.currentVector, will build parameter map too		initFittingSeries(false, filterForAll,ser_num); // will set this.currentVector, will build parameter map too

src/main/java/com/elphel/imagej/cameras/EyesisCameraParameters.java

+14 −2

Original line number	Original line	Diff line number	Diff line
	@@ -78,6 +78,7 @@ import ij.gui.GenericDialog;
	public double weightBad = 0.3; // reduce contrast of bad nodes		public double weightBad = 0.3; // reduce contrast of bad nodes
	public double weightWorst = 0.05; // reduce contrast of bad, local worst nodes		public double weightWorst = 0.05; // reduce contrast of bad, local worst nodes
	public double badNodeThreshold=0.1; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		public double badNodeThreshold=0.1; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			public double badNodeThresholdLWIR=0.2; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
	public int maxBadNeighb= 1; // maximal number of bad nodes around the corrected one to fix		public int maxBadNeighb= 1; // maximal number of bad nodes around the corrected one to fix
	public int minimalValidNodes=10; // do not use images with less than this number of non-zero nodes (after all applicable weight masks)		public int minimalValidNodes=10; // do not use images with less than this number of non-zero nodes (after all applicable weight masks)
	public int weightMultiImageMode=1; // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set to weightMultiExponent power)		public int weightMultiImageMode=1; // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set to weightMultiExponent power)
	@@ -353,6 +354,7 @@ import ij.gui.GenericDialog;
	double weightBad,		double weightBad,
	double weightWorst,		double weightWorst,
	double badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		double badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			double badNodeThresholdLWIR, // same for the low-res sensors
	int maxBadNeighb, // maximal number of bad nodes around the corrected one to fix		int maxBadNeighb, // maximal number of bad nodes around the corrected one to fix
	int minimalValidNodes,		int minimalValidNodes,
	int weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)		int weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)
	@@ -394,6 +396,7 @@ import ij.gui.GenericDialog;
	weightBad,		weightBad,
	weightWorst,		weightWorst,
	badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			badNodeThresholdLWIR, // same for the low-res sensors
	maxBadNeighb, // maximal number of bad nodes around the corrected one to fix		maxBadNeighb, // maximal number of bad nodes around the corrected one to fix
	minimalValidNodes,		minimalValidNodes,
	weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)		weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)
	@@ -435,6 +438,7 @@ import ij.gui.GenericDialog;
	double weightBad,		double weightBad,
	double weightWorst,		double weightWorst,
	double badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		double badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			double badNodeThresholdLWIR, // same for the low-res sensors
	int maxBadNeighb, // maximal number of bad nodes around the corrected one to fix		int maxBadNeighb, // maximal number of bad nodes around the corrected one to fix
	int minimalValidNodes,		int minimalValidNodes,
	int weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)		int weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)
	@@ -475,6 +479,7 @@ import ij.gui.GenericDialog;
	weightBad,		weightBad,
	weightWorst,		weightWorst,
	badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			badNodeThresholdLWIR, // same for the low-res sensors
	maxBadNeighb, // maximal number of bad nodes around the corrected one to fix		maxBadNeighb, // maximal number of bad nodes around the corrected one to fix
	minimalValidNodes,		minimalValidNodes,
	weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)		weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)
	@@ -516,6 +521,7 @@ import ij.gui.GenericDialog;
	double weightBad,		double weightBad,
	double weightWorst,		double weightWorst,
	double badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		double badNodeThreshold, // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			double badNodeThresholdLWIR, // same for the low-res sensors
	int maxBadNeighb, // maximal number of bad nodes around the corrected one to fix		int maxBadNeighb, // maximal number of bad nodes around the corrected one to fix
	int minimalValidNodes,		int minimalValidNodes,
	int weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)		int weightMultiImageMode, // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)
	@@ -544,6 +550,7 @@ import ij.gui.GenericDialog;
	this.weightBad = weightBad;		this.weightBad = weightBad;
	this.weightWorst = weightWorst;		this.weightWorst = weightWorst;
	this.badNodeThreshold=badNodeThreshold; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		this.badNodeThreshold=badNodeThreshold; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			this.badNodeThresholdLWIR=badNodeThresholdLWIR; // same for the low-res sensors
	this.maxBadNeighb=maxBadNeighb; // maximal number of bad nodes around the corrected one to fix		this.maxBadNeighb=maxBadNeighb; // maximal number of bad nodes around the corrected one to fix
	this.minimalValidNodes=minimalValidNodes;		this.minimalValidNodes=minimalValidNodes;
	this.weightMultiImageMode=weightMultiImageMode; // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)		this.weightMultiImageMode=weightMultiImageMode; // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)
	@@ -612,6 +619,7 @@ import ij.gui.GenericDialog;
	destination.weightBad = source.weightBad;		destination.weightBad = source.weightBad;
	destination.weightWorst = source.weightWorst;		destination.weightWorst = source.weightWorst;
	destination.badNodeThreshold=source.badNodeThreshold; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels		destination.badNodeThreshold=source.badNodeThreshold; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
			destination.badNodeThresholdLWIR=source.badNodeThresholdLWIR; // filter out grid nodes with difference from quadratically predicted from 8 neighbors in pixels
	destination.maxBadNeighb=source.maxBadNeighb; // maximal number of bad nodes around the corrected one to fix		destination.maxBadNeighb=source.maxBadNeighb; // maximal number of bad nodes around the corrected one to fix
	destination.minimalValidNodes=source.minimalValidNodes;		destination.minimalValidNodes=source.minimalValidNodes;
	destination.weightMultiImageMode=source.weightMultiImageMode; // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)		destination.weightMultiImageMode=source.weightMultiImageMode; // increase weight for multi-image sets (0 - do not increase, 1 - multiply by number of images in a set)
	@@ -674,6 +682,7 @@ import ij.gui.GenericDialog;
	properties.setProperty(prefix+"weightBad", this.weightBad+"");		properties.setProperty(prefix+"weightBad", this.weightBad+"");
	properties.setProperty(prefix+"weightWorst",this.weightWorst+"");		properties.setProperty(prefix+"weightWorst",this.weightWorst+"");
	properties.setProperty(prefix+"badNodeThreshold",this.badNodeThreshold+"");		properties.setProperty(prefix+"badNodeThreshold",this.badNodeThreshold+"");
			properties.setProperty(prefix+"badNodeThresholdLWIR",this.badNodeThresholdLWIR+"");
	properties.setProperty(prefix+"maxBadNeighb",this.maxBadNeighb+"");		properties.setProperty(prefix+"maxBadNeighb",this.maxBadNeighb+"");
	properties.setProperty(prefix+"minimalValidNodes",this.minimalValidNodes+"");		properties.setProperty(prefix+"minimalValidNodes",this.minimalValidNodes+"");
	properties.setProperty(prefix+"weightMultiImageMode",this.weightMultiImageMode+"");		properties.setProperty(prefix+"weightMultiImageMode",this.weightMultiImageMode+"");
	@@ -743,9 +752,10 @@ import ij.gui.GenericDialog;
	this.weightBad=Double.parseDouble(properties.getProperty(prefix+"weightBad"));		this.weightBad=Double.parseDouble(properties.getProperty(prefix+"weightBad"));
	if (properties.getProperty(prefix+"weightWorst")!=null)		if (properties.getProperty(prefix+"weightWorst")!=null)
	this.weightWorst=Double.parseDouble(properties.getProperty(prefix+"weightWorst"));		this.weightWorst=Double.parseDouble(properties.getProperty(prefix+"weightWorst"));

	if (properties.getProperty(prefix+"badNodeThreshold")!=null)		if (properties.getProperty(prefix+"badNodeThreshold")!=null)
	this.badNodeThreshold=Double.parseDouble(properties.getProperty(prefix+"badNodeThreshold"));		this.badNodeThreshold=Double.parseDouble(properties.getProperty(prefix+"badNodeThreshold"));
			if (properties.getProperty(prefix+"badNodeThresholdLWIR")!=null)
			this.badNodeThresholdLWIR=Double.parseDouble(properties.getProperty(prefix+"badNodeThresholdLWIR"));
	if (properties.getProperty(prefix+"maxBadNeighb")!=null)		if (properties.getProperty(prefix+"maxBadNeighb")!=null)
	this.maxBadNeighb=Integer.parseInt(properties.getProperty(prefix+"maxBadNeighb"));		this.maxBadNeighb=Integer.parseInt(properties.getProperty(prefix+"maxBadNeighb"));
	if (properties.getProperty(prefix+"minimalValidNodes")!=null)		if (properties.getProperty(prefix+"minimalValidNodes")!=null)
	@@ -930,6 +940,7 @@ import ij.gui.GenericDialog;
	gd.addNumericField("Scale weight of bad, locally worst nodes", this.weightWorst, 3,6,"");		gd.addNumericField("Scale weight of bad, locally worst nodes", this.weightWorst, 3,6,"");

	gd.addNumericField("Filter out grid nodes with difference from quadratically predicted from 8 neighbors", this.badNodeThreshold, 2,6,"pix");		gd.addNumericField("Filter out grid nodes with difference from quadratically predicted from 8 neighbors", this.badNodeThreshold, 2,6,"pix");
			gd.addNumericField("Same for the low-res (LWIR) sensors", this.badNodeThresholdLWIR, 2,6,"pix");
	gd.addNumericField("Maximal number of bad nodes around the corrected one to fix", this.maxBadNeighb, 0);		gd.addNumericField("Maximal number of bad nodes around the corrected one to fix", this.maxBadNeighb, 0);
	gd.addNumericField("Minimal number of valid (with all filters applied) nodes in each image",this.minimalValidNodes, 0);		gd.addNumericField("Minimal number of valid (with all filters applied) nodes in each image",this.minimalValidNodes, 0);
	gd.addNumericField("Increase weight of the multi-image sets (0 - do not increase, 1 - multiply by number of images in a set (to power ), 2 - same but remove single-image ",this.weightMultiImageMode, 0);		gd.addNumericField("Increase weight of the multi-image sets (0 - do not increase, 1 - multiply by number of images in a set (to power ), 2 - same but remove single-image ",this.weightMultiImageMode, 0);
	@@ -988,6 +999,7 @@ import ij.gui.GenericDialog;
	this.weightBad= gd.getNextNumber();		this.weightBad= gd.getNextNumber();
	this.weightWorst= gd.getNextNumber();		this.weightWorst= gd.getNextNumber();
	this.badNodeThreshold= gd.getNextNumber();		this.badNodeThreshold= gd.getNextNumber();
			this.badNodeThresholdLWIR= gd.getNextNumber();
	this.maxBadNeighb= (int) gd.getNextNumber();		this.maxBadNeighb= (int) gd.getNextNumber();
	this.minimalValidNodes= (int) gd.getNextNumber();		this.minimalValidNodes= (int) gd.getNextNumber();
	this.weightMultiImageMode=(int) gd.getNextNumber();		this.weightMultiImageMode=(int) gd.getNextNumber();

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