Commit 75365299 authored by Andrey Filippov's avatar Andrey Filippov
Browse files

matching images

parent 238bf728

src/main/java/DttRad2.java

+20 −0
Original line number Diff line number Diff line
@@ -489,6 +489,26 @@ public class DttRad2 { 
		set_unfold_2d(len);

	}

	

	// get current LT window as a 2d tile (2*size * 2*size)

	public double [] getWin2d(){

		int size = this.hwindow.length;

		int size2 = 2*size;

		double [] rslt = new double [4*size*size];

		for (int i=0; i< size; i++){

			int ia0 = i * size2;

			int ia1 = (size2 - i -1) * size2;

			for (int j=0; j< size; j++){

				double d = this.hwindow[i] * this.hwindow[j];

				rslt [ia0 + j] = d; 

				rslt [ia1 + j] = d;

				rslt [ia0 + size2 - j -1] = d; 

				rslt [ia1 + size2 - j -1] = d; 

			}

		}

		return rslt;

	}

	

	

	// Convert 2nx2n overlapping tile to n*n for dct-iv

	public double [] fold_tile(double [] x, int mode) { // x should be 2n*2n

		return fold_tile(x, 1 << (ilog2(x.length/4)/2));

src/main/java/EyesisCorrectionParameters.java

+40 −7
Original line number Diff line number Diff line
@@ -1909,6 +1909,8 @@ public class EyesisCorrectionParameters { 
  		public double     max_corr_sigma =    1.5;  // weights of points around global max to find fractional

  		                                            // pixel location by quadratic approximation

  		public double     max_corr_radius =   2.5;  // maximal distance from int max to consider

  		public int        corr_mode =         2;    // which correlation mode to use: 0 - integer max, 1 - center of mass, 2 - polynomial

  		

          // pixel location by quadratic approximation

  		public double     corr_border_contrast = 0.01; // contrast of dotted border on correlation results
@@ -1919,10 +1921,15 @@ public class EyesisCorrectionParameters { 
  		public int        tile_task_wt =      0;   // 

  		public int        tile_task_ww =      324; // 

  		public int        tile_task_wh =      242; //

  		public double     min_shot =          10.0;  // Do not adjust for shot noise if lower than

  		public double     scale_shot =        3.0;   // scale when dividing by sqrt

  		

  		public double     diff_thershold =    5.0;   // RMS difference from average to discard channel (~ 1.0 - 1/255 full scale image)

  		public double     diff_sigma =        5.0;   // RMS difference from average to reduce weights (~ 1.0 - 1/255 full scale image)

  		public double     diff_threshold =    1.5;   // RMS difference from average to discard channel (~ 1.0 - 1/255 full scale image)

  		public boolean    diff_gauss =        true;  // when averaging images, use gaussian around average as weight (false - sharp all/nothing)

  		public double     min_agree =         3.0;   // minimal number of channels to agree on a point (real number to work with fuzzy averages)

  		

  		public boolean    keep_weights =      true;  // add port weights to RGBA stack (debug feature)

  		public boolean    sharp_alpha =       false; // combining mode for alpha channel: false - treat as RGB, true - apply center 8x8 only

  		public boolean    gen_chn_img =       false; // generate shifted channel images

  		public boolean    show_nonoverlap =   true;  // show result RGBA before overlap combined (first channels, then RGBA combined?)
@@ -1970,14 +1977,20 @@ public class EyesisCorrectionParameters { 
  			properties.setProperty(prefix+"min_corr_normalized",this.min_corr_normalized +"");

  			properties.setProperty(prefix+"max_corr_sigma",   this.max_corr_sigma +"");

  			properties.setProperty(prefix+"max_corr_radius",  this.max_corr_radius +"");

  			properties.setProperty(prefix+"corr_mode",        this.corr_mode+"");

  			properties.setProperty(prefix+"corr_border_contrast", this.corr_border_contrast +"");

  			properties.setProperty(prefix+"tile_task_op",     this.tile_task_op+"");

  			properties.setProperty(prefix+"tile_task_wl",     this.tile_task_wl+"");

  			properties.setProperty(prefix+"tile_task_wt",     this.tile_task_wt+"");

  			properties.setProperty(prefix+"tile_task_ww",     this.tile_task_ww+"");

  			properties.setProperty(prefix+"tile_task_wh",     this.tile_task_wh+"");

  			properties.setProperty(prefix+"diff_thershold",   this.diff_thershold +"");

  			properties.setProperty(prefix+"min_shot",       this.min_shot +"");

  			properties.setProperty(prefix+"scale_shot",       this.scale_shot +"");

  			properties.setProperty(prefix+"diff_sigma",       this.diff_sigma +"");

  			properties.setProperty(prefix+"diff_threshold",   this.diff_threshold +"");

			properties.setProperty(prefix+"diff_gauss",       this.diff_gauss+"");

  			properties.setProperty(prefix+"min_agree",        this.min_agree +"");

			properties.setProperty(prefix+"keep_weights",     this.keep_weights+"");

			properties.setProperty(prefix+"sharp_alpha",      this.sharp_alpha+"");

			properties.setProperty(prefix+"gen_chn_img",      this.gen_chn_img+"");

			properties.setProperty(prefix+"show_nonoverlap",  this.show_nonoverlap+"");
@@ -2022,14 +2035,20 @@ public class EyesisCorrectionParameters { 
  			if (properties.getProperty(prefix+"min_corr_normalized")!=null)this.min_corr_normalized=Double.parseDouble(properties.getProperty(prefix+"min_corr_normalized"));

  			if (properties.getProperty(prefix+"max_corr_sigma")!=null) this.max_corr_sigma=Double.parseDouble(properties.getProperty(prefix+"max_corr_sigma"));

  			if (properties.getProperty(prefix+"max_corr_radius")!=null) this.max_corr_radius=Double.parseDouble(properties.getProperty(prefix+"max_corr_radius"));

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

  			if (properties.getProperty(prefix+"corr_border_contrast")!=null) this.corr_border_contrast=Double.parseDouble(properties.getProperty(prefix+"corr_border_contrast"));

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

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

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

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

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

  			if (properties.getProperty(prefix+"diff_thershold")!=null) this.diff_thershold=Double.parseDouble(properties.getProperty(prefix+"diff_thershold"));

  			if (properties.getProperty(prefix+"diff_gauss")!=null)     this.diff_gauss=Boolean.parseBoolean(properties.getProperty(prefix+"v"));

  			if (properties.getProperty(prefix+"min_shot")!=null)     this.min_shot=Double.parseDouble(properties.getProperty(prefix+"min_shot"));

  			if (properties.getProperty(prefix+"scale_shot")!=null)     this.scale_shot=Double.parseDouble(properties.getProperty(prefix+"scale_shot"));

  			if (properties.getProperty(prefix+"diff_sigma")!=null)     this.diff_sigma=Double.parseDouble(properties.getProperty(prefix+"diff_sigma"));

  			if (properties.getProperty(prefix+"diff_threshold")!=null) this.diff_threshold=Double.parseDouble(properties.getProperty(prefix+"diff_threshold"));

  			if (properties.getProperty(prefix+"diff_gauss")!=null)     this.diff_gauss=Boolean.parseBoolean(properties.getProperty(prefix+"diff_gauss"));

  			if (properties.getProperty(prefix+"min_agree")!=null)      this.min_agree=Double.parseDouble(properties.getProperty(prefix+"min_agree"));

  			if (properties.getProperty(prefix+"keep_weights")!=null)   this.keep_weights=Boolean.parseBoolean(properties.getProperty(prefix+"keep_weights"));

  			if (properties.getProperty(prefix+"sharp_alpha")!=null)    this.sharp_alpha=Boolean.parseBoolean(properties.getProperty(prefix+"sharp_alpha"));

  			if (properties.getProperty(prefix+"gen_chn_img")!=null)    this.gen_chn_img=Boolean.parseBoolean(properties.getProperty(prefix+"gen_chn_img"));

  			if (properties.getProperty(prefix+"show_nonoverlap")!=null)this.show_nonoverlap=Boolean.parseBoolean(properties.getProperty(prefix+"show_nonoverlap"));
@@ -2076,6 +2095,7 @@ public class EyesisCorrectionParameters { 
  			gd.addNumericField("Minimal correlation value to consider valid when normalizing results",    this.min_corr_normalized,  6);

  			gd.addNumericField("Sigma for weights of points around global max to find fractional",        this.max_corr_sigma,  3);

  			gd.addNumericField("Maximal distance from int max to consider",                               this.max_corr_radius,  3);

  			gd.addNumericField("Correlation mode: 0 - integer max, 1 - center of mass, 2 - polynomial",   this.corr_mode,            0);

  			gd.addNumericField("Contrast of dotted border on correlation results",                        this.corr_border_contrast,  6);

  			gd.addMessage("--- tiles tasks ---");

  			gd.addNumericField("Tile operations bits: +(0..f) - images, +(00.f0) - process pairs +256, ... ",  this.tile_task_op,            0);
@@ -2083,8 +2103,15 @@ public class EyesisCorrectionParameters { 
  			gd.addNumericField("Tile operations window top",                                              this.tile_task_wt,            0);

  			gd.addNumericField("Tile operations window width",                                            this.tile_task_ww,            0);

  			gd.addNumericField("Tile operations window height",                                           this.tile_task_wh,            0);

  			gd.addNumericField("RMS difference from average to discard channel (255 full scale image)",   this.diff_thershold,  4);

  			

  			gd.addNumericField("Do not adjust for shot noise (~sqrt) if lower than this",                 this.min_shot,  4);

  			gd.addNumericField("Scale when dividing by sqrt for shot noise compensation of pixel differences (<0 - disable)", this.scale_shot,  4);

  			

  			gd.addNumericField("RMS difference from average to reduce weights (255 full scale image)",    this.diff_sigma,  4);

  			gd.addNumericField("RMS difference from average in sigmas to discard channel",                this.diff_threshold,  4);

  			gd.addCheckbox    ("Gaussian as weight when averaging images (false - sharp all/nothing)",    this.diff_gauss);

  			gd.addNumericField("Minimal number of channels to agree on a point (real number to work with fuzzy averages)",   this.min_agree,  2);

  			gd.addCheckbox    ("Add port weights to RGBA stack (debug feature)",                          this.keep_weights);

  			gd.addCheckbox    ("Alpha channel: use center 8x8 (unchecked - treat same as RGB)",           this.sharp_alpha);

  			gd.addCheckbox    ("Generate shifted channel images",                                         this.gen_chn_img);

  			gd.addCheckbox    ("Show result RGBA before overlap combined",                                this.show_nonoverlap);
@@ -2131,14 +2158,20 @@ public class EyesisCorrectionParameters { 
  			this.min_corr_normalized=   gd.getNextNumber();

  			this.max_corr_sigma=        gd.getNextNumber();

  			this.max_corr_radius=       gd.getNextNumber();

  			this.corr_mode=       (int) gd.getNextNumber();

  			this.corr_border_contrast=  gd.getNextNumber();

  			this.tile_task_op=    (int) gd.getNextNumber();

  			this.tile_task_wl=    (int) gd.getNextNumber();

  			this.tile_task_wt=    (int) gd.getNextNumber();

  			this.tile_task_ww=    (int) gd.getNextNumber();

  			this.tile_task_wh=    (int) gd.getNextNumber();

  			this.diff_thershold=        gd.getNextNumber();

  			this.min_shot=              gd.getNextNumber();

  			this.scale_shot=            gd.getNextNumber();

  			this.diff_sigma=            gd.getNextNumber();

  			this.diff_threshold=        gd.getNextNumber();

  			this.diff_gauss=            gd.getNextBoolean();

  			this.min_agree=             gd.getNextNumber();

  			this.keep_weights=          gd.getNextBoolean();

  			this.sharp_alpha=           gd.getNextBoolean();

  			this.gen_chn_img=           gd.getNextBoolean();

  			this.show_nonoverlap=       gd.getNextBoolean();

src/main/java/EyesisDCT.java

+51 −38
Original line number Diff line number Diff line
@@ -4821,8 +4821,9 @@ public class EyesisDCT { 
		  // for testing defined for a window, later the tiles to process will be calculated based on previous passes results

		  int [][] tile_op = new int [tilesY][tilesX]; // all zero

		  int txl =  clt_parameters.tile_task_wl;

		  int txr =  txl + clt_parameters.tile_task_wl;

		  int tyt =  clt_parameters.tile_task_wl;

		  int txr =  txl + clt_parameters.tile_task_ww;

		  

		  int tyt =  clt_parameters.tile_task_wt;

		  int tyb =  tyt + clt_parameters.tile_task_wh;

		  if      (txl < 0)       txl = 0;

		  else if (txl >= tilesX) txl = tilesX - 1;
@@ -4841,6 +4842,14 @@ public class EyesisDCT { 
				  tile_op[i][j] = clt_parameters.tile_task_op;

			  }

		  }

		  if (debugLevel > -1){

			  System.out.println("clt_parameters.tile_task_wl="+clt_parameters.tile_task_wl );

			  System.out.println("clt_parameters.tile_task_wt="+clt_parameters.tile_task_wt );

			  System.out.println("clt_parameters.tile_task_ww="+clt_parameters.tile_task_ww );

			  System.out.println("clt_parameters.tile_task_wh="+clt_parameters.tile_task_wh );

			  System.out.println("tyt="+tyt+" tyb="+tyb+" txl="+txl+" txr="+txr );

		  }

		  

		  //TODO: Add array of default disparity - use for combining images in force disparity mode (no correlation), when disparity is predicted from other tiles



		  double [][][][]     clt_corr_combo =   null;
@@ -4849,7 +4858,7 @@ public class EyesisDCT { 
		  // undecided, so 2 modes of combining alpha - same as rgb, or use center tile only

		  if (clt_parameters.correlate){

			  clt_corr_combo =    new double [2][tilesY][tilesX][];

			  texture_tiles =     new double [tilesY][tilesX]["RGBA".length()][];

			  texture_tiles =     new double [tilesY][tilesX][][]; // ["RGBA".length()][];

			  for (int i = 0; i < tilesY; i++){

				  for (int j = 0; j < tilesX; j++){

					  clt_corr_combo[0][i][j] = null;
@@ -4867,6 +4876,7 @@ public class EyesisDCT { 
			  }

		  }

		  double [][] disparity_map = new double [8][]; //[0] -residual disparity, [1] - orthogonal (just for debugging)

		  double min_corr_selected = clt_parameters.corr_normalize? clt_parameters.min_corr_normalized: clt_parameters.min_corr;

		  double [][][][][][] clt_data = image_dtt.clt_aberrations_quad_corr(

				  tile_op,                      // per-tile operation bit codes

				  clt_parameters.disparity,     // final double            disparity,
@@ -4883,11 +4893,19 @@ public class EyesisDCT { 
				  clt_parameters.corr_red,

				  clt_parameters.corr_blue,

				  clt_parameters.corr_sigma,

				  clt_parameters.corr_mask,

//				  clt_parameters.corr_mask,

				  clt_parameters.corr_normalize, // normalize correlation results by rms 

				  clt_parameters.corr_normalize? clt_parameters.min_corr_normalized: clt_parameters.min_corr, // 0.0001; // minimal correlation value to consider valid 

				  min_corr_selected, // 0.0001; // minimal correlation value to consider valid 

				  clt_parameters.max_corr_sigma,// 1.5;  // weights of points around global max to find fractional

				  clt_parameters.max_corr_radius,

				  clt_parameters.corr_mode,     // Correlation mode: 0 - integer max, 1 - center of mass, 2 - polynomial

				  clt_parameters.min_shot,       // 10.0;  // Do not adjust for shot noise if lower than

				  clt_parameters.scale_shot,     // 3.0;   // scale when dividing by sqrt ( <0 - disable correction)

				  clt_parameters.diff_sigma,     // 5.0;//RMS difference from average to reduce weights (~ 1.0 - 1/255 full scale image)

				  clt_parameters.diff_threshold, // 5.0;   // RMS difference from average to discard channel (~ 1.0 - 1/255 full scale image)

				  clt_parameters.diff_gauss,     // true;  // when averaging images, use gaussian around average as weight (false - sharp all/nothing)

				  clt_parameters.min_agree,      // 3.0;   // minimal number of channels to agree on a point (real number to work with fuzzy averages)

				  clt_parameters.keep_weights,   // Add port weights to RGBA stack (debug feature)

				  geometryCorrection,           // final GeometryCorrection  geometryCorrection,

				  clt_kernels,                  // final double [][][][][][] clt_kernels, // [channel_in_quad][color][tileY][tileX][band][pixel] , size should match image (have 1 tile around)

				  clt_parameters.kernel_step,
@@ -4902,16 +4920,18 @@ public class EyesisDCT { 
				  //				  (clt_parameters.dbg_mode & 256) != 0, // transpose convolve

				  threadsMax,

				  debugLevel);



		  if (debugLevel > -1){

			  System.out.println("clt_data.length="+clt_data.length+" clt_data[0].length="+clt_data[0].length

					  +" clt_data[0][0].length="+clt_data[0][0].length+" clt_data[0][0][0].length="+

					  clt_data[0][0][0].length);

		  }

//		  +" clt_data[0][0][0][0].length="+clt_data[0][0][0][0].length+

//				  " clt_data[0][0][0][0][0].length="+clt_data[0][0][0][0][0].length);

		  // visualize texture tiles as RGBA slices

		  double [][] texture_nonoverlap = null;

		  double [][] texture_overlap = null;

		  String [] rgba_titles = {"red","green","blue","alpha"};

		  String [] rgba_titles = {"red","blue","green","alpha"};

		  String [] rgba_weights_titles = {"red","blue","green","alpha","port0","port1","port2","port3","r-rms","b-rms","g-rms","w-rms"};

		  if (texture_tiles != null){

			  if (clt_parameters.show_nonoverlap){

				  texture_nonoverlap = image_dtt.combineRGBATiles(
@@ -4927,7 +4947,7 @@ public class EyesisDCT { 
						  tilesY * (2 * clt_parameters.transform_size),

						  true,

						  name + "-TXTNOL-D"+clt_parameters.disparity,

						  rgba_titles );

						  (clt_parameters.keep_weights?rgba_weights_titles:rgba_titles));



			  }

			  if (clt_parameters.show_overlap){
@@ -4944,8 +4964,7 @@ public class EyesisDCT { 
						  tilesY * clt_parameters.transform_size,

						  true,

						  name + "-TXTOL-D"+clt_parameters.disparity,

						  rgba_titles );



						  (clt_parameters.keep_weights?rgba_weights_titles:rgba_titles));

			  }



		  }
@@ -5037,7 +5056,7 @@ public class EyesisDCT { 
					  System.out.println("--tilesX="+tilesX);

					  System.out.println("--tilesY="+tilesY);

				  }

				  if (debugLevel > 1){

				  if (debugLevel > 0){

					  double [][] clt = new double [clt_data[iQuad].length*4][];

					  for (int chn = 0; chn < clt_data[iQuad].length; chn++) {

						  double [][] clt_set = image_dtt.clt_dbg(
@@ -5067,13 +5086,7 @@ public class EyesisDCT { 
							  debugLevel);



				  }

				  if (debugLevel > 0) sdfa_instance.showArrays( // -1

						  iclt_data,

						  (tilesX + 0) * clt_parameters.transform_size,

						  (tilesY + 0) * clt_parameters.transform_size,

						  true,

						  results[iQuad].getTitle()+"-rbg_sigma");

				  if (debugLevel > 0) sdfa_instance.showArrays(iclt_data,

				  if (debugLevel > -1) sdfa_instance.showArrays(iclt_data, 

						  (tilesX + 0) * clt_parameters.transform_size,

						  (tilesY + 0) * clt_parameters.transform_size,

						  true,

src/main/java/ImageDtt.java

+571 −82

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