more development

src/main/java/Eyesis_Correction.java

@@ -496,6 +496,7 @@ private Panel panel1,
 			addButton("CLT process files",         panelClt1, color_process);
 			addButton("CLT process sets",          panelClt1, color_process);
 			addButton("CLT process quads",         panelClt1, color_process);
+			addButton("CLT process corr",          panelClt1, color_process);
 			add(panelClt1);
 		}
 		pack();
@@ -4022,6 +4023,7 @@ private Panel panel1,
             for (int chn = 0; chn < clt_corr.length; chn++) {
             	corr_rslt[chn] = image_dtt.corr_dbg(
             			corr_tiles[chn],
+            			CLT_PARAMETERS.corr_border_contrast,
             			THREADS_MAX,
             			DEBUG_LEVEL);
             	
@@ -4413,6 +4415,104 @@ private Panel panel1,
         return;
         
 
+    } else if (label.equals("CLT process corr")) {
+    	DEBUG_LEVEL=MASTER_DEBUG_LEVEL;
+    	EYESIS_CORRECTIONS.setDebug(DEBUG_LEVEL);
+        if (EYESIS_DCT == null){
+        	EYESIS_DCT = new  EyesisDCT (
+        			EYESIS_CORRECTIONS,
+        			CORRECTION_PARAMETERS,
+        			DCT_PARAMETERS);
+        	if (DEBUG_LEVEL > 0){
+        		System.out.println("Created new EyesisDCT instance, will need to read CLT kernels");
+        	}
+        }
+    	String configPath=null;
+    	if (EYESIS_CORRECTIONS.correctionsParameters.saveSettings) {
+    		configPath=EYESIS_CORRECTIONS.correctionsParameters.selectResultsDirectory(
+    				true,
+    				true);
+    		if (configPath==null){
+    			String msg="No results directory selected, command aborted";
+    			System.out.println("Warning: "+msg);
+    			IJ.showMessage("Warning",msg);
+    			return;
+    		}
+    		configPath+=Prefs.getFileSeparator()+"autoconfig";
+    		try {
+    			saveTimestampedProperties(
+    					configPath,      // full path or null
+    					null, // use as default directory if path==null 
+    					true,
+    					PROPERTIES);
+
+    		} catch (Exception e){
+    			String msg="Failed to save configuration to "+configPath+", command aborted";
+    			System.out.println("Error: "+msg);
+    			IJ.showMessage("Error",msg);
+    			return;
+    		}
+    	}      
+        
+        EYESIS_CORRECTIONS.initSensorFiles(DEBUG_LEVEL);
+        int numChannels=EYESIS_CORRECTIONS.getNumChannels();
+        NONLIN_PARAMETERS.modifyNumChannels(numChannels);
+        CHANNEL_GAINS_PARAMETERS.modifyNumChannels(numChannels);
+
+        if (!EYESIS_DCT.CLTKernelsAvailable()){
+        	if (DEBUG_LEVEL > 0){
+        		System.out.println("Reading CLT kernels");
+        	}
+            EYESIS_DCT.readCLTKernels(
+            		CLT_PARAMETERS,
+                    THREADS_MAX,
+                    UPDATE_STATUS, // update status info
+            		DEBUG_LEVEL);
+
+            if (DEBUG_LEVEL > 1){
+            	EYESIS_DCT.showCLTKernels(
+            			THREADS_MAX,
+            			UPDATE_STATUS, // update status info
+            			DEBUG_LEVEL);
+        	}
+        }
+
+        if (!EYESIS_DCT.geometryCorrectionAvailable()){
+        	if (DEBUG_LEVEL > 0){
+        		System.out.println("Calculating geometryCorrection");
+        	}
+        	if (!EYESIS_DCT.initGeometryCorrection(DEBUG_LEVEL+2)){
+        		return;
+        	}
+        }
+        
+///========================================        
+        
+        EYESIS_DCT.processCLTQuadCorrs(
+        		CLT_PARAMETERS,  // EyesisCorrectionParameters.DCTParameters           dct_parameters,
+        		DEBAYER_PARAMETERS, //EyesisCorrectionParameters.DebayerParameters     debayerParameters,
+        		NONLIN_PARAMETERS, //EyesisCorrectionParameters.NonlinParameters       nonlinParameters,
+        		COLOR_PROC_PARAMETERS, //EyesisCorrectionParameters.ColorProcParameters colorProcParameters,
+        		CHANNEL_GAINS_PARAMETERS, //CorrectionColorProc.ColorGainsParameters     channelGainParameters,
+        		RGB_PARAMETERS, //EyesisCorrectionParameters.RGBParameters             rgbParameters,
+        		EQUIRECTANGULAR_PARAMETERS, // EyesisCorrectionParameters.EquirectangularParameters equirectangularParameters,
+        		CONVOLVE_FFT_SIZE, //int          convolveFFTSize, // 128 - fft size, kernel size should be size/2
+        		THREADS_MAX, //final int          threadsMax,  // maximal number of threads to launch                         
+        		UPDATE_STATUS, //final boolean    updateStatus,
+        		DEBUG_LEVEL); //final int        debugLevel);
+        
+        if (configPath!=null) {
+        	saveTimestampedProperties( // save config again
+        			configPath,      // full path or null
+        			null, // use as default directory if path==null 
+        			true,
+        			PROPERTIES);
+        }
+        return;
+        
+        
+        
+        
     	
 // End of buttons code    	
     }

src/main/java/GeometryCorrection.java

@@ -330,8 +330,10 @@ public class GeometryCorrection {
 		double [] a={this.distortionC,this.distortionB,this.distortionA,this.distortionA5,this.distortionA6,this.distortionA7,this.distortionA8};
 		for (int i = 0; i < numSensors; i++){
 			// non-distorted XY of the shifted location of the individual sensor
-			double pXci = pXc + disparity *  this.rXY[i][0]; // in pixels
-			double pYci = pYc + disparity *  this.rXY[i][1];
+//			double pXci = pXc + disparity *  this.rXY[i][0]; // in pixels
+//			double pYci = pYc + disparity *  this.rXY[i][1];
+			double pXci = pXc - disparity *  this.rXY[i][0]; // in pixels
+			double pYci = pYc - disparity *  this.rXY[i][1];
 			// calculate back to distorted
 			double rNDi = Math.sqrt(pXci*pXci + pYci*pYci); // in pixels
 			//		Rdist/R=A8*R^7+A7*R^6+A6*R^5+A5*R^4+A*R^3+B*R^2+C*R+(1-A6-A7-A6-A5-A-B-C)");

src/main/java/PolynomialApproximation.java

@@ -163,11 +163,17 @@ public class PolynomialApproximation {
 
 		
 	}
+
 	  public double[] quadraticMax2d (double [][][] data){
 		  return quadraticMax2d (data,1.0E-15);
 	  }
-	  public double[] quadraticMax2d (double [][][] data,double thresholdQuad){
-		  double [][] coeff=quadraticApproximation(data, false);
+
+	  public double[] quadraticMax2d (double [][][] data, double thresholdQuad){
+		  return quadraticMax2d (data,thresholdQuad, debugLevel);
+	  }
+
+	  public double[] quadraticMax2d (double [][][] data,double thresholdQuad, int debugLevel){
+		  double [][] coeff=quadraticApproximation(data, false, 1.0E-20,  thresholdQuad,debugLevel);
 		  if (coeff==null) return null;
 		  if (coeff[0].length<6) return null;
 		  double [][] aM={
@@ -203,16 +209,28 @@ public class PolynomialApproximation {
 	 * returns null if not enough data even for the linear approximation
 	 
 	 */
-	
 	   public double [][] quadraticApproximation(
 			   double [][][] data,
-			   boolean forceLinear  // use linear approximation
+			   boolean forceLinear)  // use linear approximation
+			   {
+		   return  quadraticApproximation(
+				   data,
+				   forceLinear,  // use linear approximation
+				   1.0E-10,  // threshold ratio of matrix determinant to norm for linear approximation (det too low - fail) 11.0E-10 failed where it shouldn't?
+				   1.0E-15,  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
+				   this.debugLevel);
+			   }
+	   public double [][] quadraticApproximation(
+			   double [][][] data,
+			   boolean forceLinear,  // use linear approximation
+			   int debugLevel
 			   ){
 		   return  quadraticApproximation(
 				   data,
 				   forceLinear,  // use linear approximation
 				   1.0E-10,  // threshold ratio of matrix determinant to norm for linear approximation (det too low - fail) 11.0E-10 failed where it shouldn't?
-				   1.0E-15);  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
+				   1.0E-15,  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
+				   debugLevel);
 /*				   
 				   1.0E-12,  // threshold ratio of matrix determinant to norm for linear approximation (det too low - fail) 11.0E-10 failed where it shouldn't?
 				   1.0E-20);  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
@@ -222,9 +240,24 @@ public class PolynomialApproximation {
 			   double [][][] data,
 			   boolean forceLinear,  // use linear approximation
 			   double thresholdLin,  // threshold ratio of matrix determinant to norm for linear approximation (det too low - fail)
-				   double thresholdQuad  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
+			   double thresholdQuad)  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
+			   {
+		   return  quadraticApproximation(
+				   data,
+				   forceLinear,  // use linear approximation
+				   1.0E-10,  // threshold ratio of matrix determinant to norm for linear approximation (det too low - fail) 11.0E-10 failed where it shouldn't?
+				   1.0E-15,  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
+				   this.debugLevel);
+	   }
+	   
+	   public double [][] quadraticApproximation(
+				   double [][][] data,
+				   boolean forceLinear,  // use linear approximation
+				   double thresholdLin,  // threshold ratio of matrix determinant to norm for linear approximation (det too low - fail)
+				   double thresholdQuad,  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
+				   int debugLevel
 				   ){
-			   if (this.debugLevel>3) System.out.println("quadraticApproximation(...), debugLevel="+this.debugLevel+":");
+			   if (debugLevel>3) System.out.println("quadraticApproximation(...), debugLevel="+debugLevel+":");
 	/* ix, iy - the location of the point with maximal value. We'll approximate the vicinity of that maximum using a
 	 * second degree polynomial:
 	   Z(x,y)~=A*x^2+B*y^2+C*x*y+D*x+E*y+F
@@ -365,7 +398,7 @@ public class PolynomialApproximation {
 					   {S10,S01,S00}};
 			   Matrix M=new Matrix (mAarrayL);
 			   Matrix Z;
-	 	   	   if (this.debugLevel>3) System.out.println(">>> n="+n+" det_lin="+M.det()+" norm_lin="+normMatix(mAarrayL));
+	 	   	   if (debugLevel>3) System.out.println(">>> n="+n+" det_lin="+M.det()+" norm_lin="+normMatix(mAarrayL));
 	 	   	   double nmL=normMatix(mAarrayL);
 			   if ((nmL==0.0) || (Math.abs(M.det())/nmL<thresholdLin)){
 // return average value for each channel
@@ -398,10 +431,17 @@ public class PolynomialApproximation {
 					   {S21,S03,S12,S11,S02,S01},
 					   {S20,S02,S11,S10,S01,S00}};
 			   M=new Matrix (mAarrayQ);
-	 	   	   if (debugLevel>3) System.out.println("    n="+n+" det_quad="+M.det()+" norm_quad="+normMatix(mAarrayQ)+" data.length="+data.length);
+	 	   	   if (debugLevel>3) {
+	 	   		   System.out.println("    n="+n+" det_quad="+M.det()+" norm_quad="+normMatix(mAarrayQ)+" data.length="+data.length);
+	 	   		   M.print(10,5);
+	 	   	   }
 	 	   	   double nmQ=normMatix(mAarrayQ);
 			   if ((nmQ==0.0) || (Math.abs(M.det())/normMatix(mAarrayQ)<thresholdQuad)) {
-				   if (debugLevel>0) System.out.println("Using linear approximation, M.det()="+M.det()+" normMatix(mAarrayQ)="+normMatix(mAarrayQ)); //did not happen
+				   if (debugLevel>0) System.out.println("Using linear approximation, M.det()="+M.det()+
+						   " normMatix(mAarrayQ)="+normMatix(mAarrayQ)+
+						   ", thresholdQuad="+thresholdQuad+
+						   ", nmQ="+nmQ+
+						   ", Math.abs(M.det())/normMatix(mAarrayQ)="+(Math.abs(M.det())/normMatix(mAarrayQ))); //did not happen
 				   return ABCDEF; // not enough data for the quadratic approximation, return linear
 			   }
 //			   double [] zAarrayQ={SZ20,SZ02,SZ11,SZ10,SZ01,SZ00};