Added temporal unsharp mask

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

@@ -707,6 +707,9 @@ min_str_neib_fpn	0.35
     public boolean  cuas_smooth =        true;    // used cosine window when averaging correlations
     public int      cuas_corr_pairs =     50;     // number of correlation pairs to accumulate
     public int      cuas_corr_offset =    20;     // offset between motion detection pairs
+    public int      cuas_temporal_um =    100;    // temporal "unsharp mask" - subtract running
+    public double   cuas_tum_threshold =  5.0;    // if >0, remove outliers frim the running average and recalculate RA
+    
     public int      cuas_precorr_ra =     10;     // rolling average before correlation
     public int      cuas_corr_step =      5;      // correlation step when using rolling average
     
@@ -2210,6 +2213,10 @@ min_str_neib_fpn	0.35
 				"The number of correlation pairs to accumulate.");
 		gd.addNumericField("Pairs offset",                           this.cuas_corr_offset, 0,3,"scenes",
 				"Offset between the correlation pairs");
+		gd.addNumericField("Temporal unsharp mask length",           this.cuas_temporal_um, 0,3,"scenes",
+				"Subtract running average this long.");
+		gd.addNumericField("Temporal UM threshold",                  this.cuas_tum_threshold, 5,8,"",
+				"Remove outlier pixels that differ from the running average by more than this (to later re-calculate running average excluding those pixels.");
 
 		gd.addNumericField("Pre-correlation running average",        this.cuas_precorr_ra, 0,3,"scenes",
 				"Smoothing input data by running average before correlation for motion vectors calculations. Target extraction wil still use individual scenes.");
@@ -3323,6 +3330,9 @@ min_str_neib_fpn	0.35
 		this.cuas_corr_pairs =    (int) gd.getNextNumber();
 		this.cuas_corr_offset =   (int) gd.getNextNumber();
 		
+		this.cuas_temporal_um =   (int) gd.getNextNumber();
+		this.cuas_tum_threshold =       gd.getNextNumber();
+		
 		this.cuas_precorr_ra =    (int) gd.getNextNumber();
 		this.cuas_corr_step =     (int) gd.getNextNumber();
 		
@@ -4285,6 +4295,8 @@ min_str_neib_fpn	0.35
         properties.setProperty(prefix+"cuas_smooth",          this.cuas_smooth+"");         // boolean
         properties.setProperty(prefix+"cuas_corr_pairs",      this.cuas_corr_pairs+"");     // int
 		properties.setProperty(prefix+"cuas_corr_offset",     this.cuas_corr_offset+"");    // int
+		properties.setProperty(prefix+"cuas_temporal_um",     this.cuas_temporal_um+"");    // int
+		properties.setProperty(prefix+"cuas_tum_threshold",   this.cuas_tum_threshold+"");  // double
 		
 		properties.setProperty(prefix+"cuas_precorr_ra",      this.cuas_precorr_ra+"");     // int
 		properties.setProperty(prefix+"cuas_corr_step",       this.cuas_corr_step+"");      // int
@@ -5215,6 +5227,8 @@ min_str_neib_fpn	0.35
 		if (properties.getProperty(prefix+"cuas_smooth")!=null)          this.cuas_smooth=Boolean.parseBoolean(properties.getProperty(prefix+"cuas_smooth"));
 		if (properties.getProperty(prefix+"cuas_corr_pairs")!=null)      this.cuas_corr_pairs=Integer.parseInt(properties.getProperty(prefix+"cuas_corr_pairs"));
 		if (properties.getProperty(prefix+"cuas_corr_offset")!=null)     this.cuas_corr_offset=Integer.parseInt(properties.getProperty(prefix+"cuas_corr_offset"));
+		if (properties.getProperty(prefix+"cuas_temporal_um")!=null)     this.cuas_temporal_um=Integer.parseInt(properties.getProperty(prefix+"cuas_temporal_um"));
+		if (properties.getProperty(prefix+"cuas_tum_threshold")!=null)   this.cuas_tum_threshold=Double.parseDouble(properties.getProperty(prefix+"cuas_tum_threshold"));
 		
 		if (properties.getProperty(prefix+"cuas_precorr_ra")!=null)      this.cuas_precorr_ra=Integer.parseInt(properties.getProperty(prefix+"cuas_precorr_ra"));
 		if (properties.getProperty(prefix+"cuas_corr_step")!=null)       this.cuas_corr_step=Integer.parseInt(properties.getProperty(prefix+"cuas_corr_step"));
@@ -6148,6 +6162,9 @@ min_str_neib_fpn	0.35
 		imp.cuas_smooth =           this.cuas_smooth;
 		imp.cuas_corr_pairs =       this.cuas_corr_pairs;
 		imp.cuas_corr_offset =      this.cuas_corr_offset;
+		imp.cuas_temporal_um =      this.cuas_temporal_um;
+		imp.cuas_tum_threshold =    this.cuas_tum_threshold;
+		
 		imp.cuas_precorr_ra =       this.cuas_precorr_ra;
 		imp.cuas_corr_step =        this.cuas_corr_step;
 		imp.cuas_half_step =        this.cuas_half_step;