CLAUDE: Add 5D fine-velocity convolution to CuasDetectRT.detectTargets()

Add convolve3d() (kernel5d) at level-0 before the temporal pyramid loop
and at each pyramid level nlev+1 inside the loop, mirroring the existing
3D3 coarse-velocity pattern. Output saved as CONV5D hyperstack when
debugLevel > -4. Add getNumHist() getter to CuasRTUtils.
Co-authored-by: Claude <claude@elphel.com>

src/main/java/com/elphel/imagej/cuas/rt/CuasDetectRT.java

@@ -19,6 +19,7 @@ public class CuasDetectRT {
 	public static final String SUFFIX_LOG = "-LoG";
 	public static final String SUFFIX_CONV2D = "-CONV2D";
 	public static final String SUFFIX_CONV3D3 = "-CONV3D3";
+	public static final String SUFFIX_CONV5D =  "-CONV5D";
 	public static final String [] CONV3D3_MODES = {"plain", "winner", "power"};
 	public static final int CONV3D3_MODE_PLAIN =  0;
 	public static final int CONV3D3_MODE_WINNER = 1;
@@ -256,12 +257,6 @@ public class CuasDetectRT {
    					title_conv3d3);   // String        title)
        		QuadCLTCPU.saveImagePlusInDirectory(imp_3d3, getModelDirectory());
    		}
-       	
-   		
-   		
-   		
-   		
-   		
    		
        	// building pyramid
    		int pyramid_levels = 	clt_parameters.imp.curt_pyramid;
@@ -269,6 +264,7 @@ public class CuasDetectRT {
    		double [][][]   dpixels_pyramid =     new double [pyramid_levels][][];
    		String [][]     ts_pyramid =          new String [pyramid_levels][];
    		double [][][][] dpixels_3d3_pyramid = new double [pyramid_levels][][][];
+   		double [][][][][] dpixels_5d_pyramid = new double [pyramid_levels][][][][];
    		ts_pyramid[0] =          getTimeStamps(1);
    		dpixels_3d3_pyramid[0] = dpixels_3d3;
    		dpixels_pyramid[0] = new double[dpixels_log.length-1][width*height];
@@ -281,16 +277,31 @@ public class CuasDetectRT {
 		}
 //   		System.arraycopy(dpixels_log, 1, dpixels_pyramid[0], 0, dpixels_pyramid[0].length);
    		int center9 = 4;
-   		for (int nlev = 0; nlev < pyramid_levels; nlev++) {
-   			/*
-   			// copy centers
-   			dpixels_pyramid[nlev] = new double [dpixels_3d3_pyramid[nlev].length][width*height];
-   			for (int nseq = 0; nseq < dpixels_pyramid[nlev].length; nseq++) {
-   				for (int npix = 0; npix <  dpixels_pyramid[nlev][nseq].length; npix++) {
-   					dpixels_pyramid[nlev][nseq][npix] = dpixels_3d3_pyramid[nlev][nseq][npix][center9]; 
-   				}
+   		int num_hist_5d = cuasRTUtils.getNumHist();
+   		boolean save_5d_pixels = debugLevel > -4;
+   		String title_conv5d = getBaseName()+SUFFIX_CONV5D+"-PSF"+d2s(cuasRTUtils.getPsfRadius())+
+   				"-KR"+d2s(cuasRTUtils.getKernel2dRadius())+"-NHIST"+num_hist_5d+
+   				"-VELRAD"+curt_vel_radius+"-VELDEC"+curt_vel_decimate;
+   		// Level-0 5D convolution (fine velocity from coarse-velocity history)
+   		int num_5d_lev0 = Math.max(0, dpixels_3d3.length - num_hist_5d + 1);
+   		dpixels_5d_pyramid[0] = new double[num_5d_lev0][][][];
+   		String[] ts_5d_lev0 = new String[num_5d_lev0];
+   		for (int n5d = 0; n5d < num_5d_lev0; n5d++) {
+   			double[][][] window = new double[num_hist_5d][][];
+   			for (int h = 0; h < num_hist_5d; h++) {
+   				window[h] = dpixels_3d3[n5d + num_hist_5d - 1 - h];
    			}
-   			*/
+   			dpixels_5d_pyramid[0][n5d] = cuasRTUtils.convolve3d(window, null);
+   			ts_5d_lev0[n5d] = ts_pyramid[0][n5d + num_hist_5d - 1];
+   		}
+   		if (save_5d_pixels && num_5d_lev0 > 0) {
+   			ImagePlus imp_5d = cuasRTUtils.showConvKernel5d(
+   					dpixels_5d_pyramid[0],
+   					ts_5d_lev0,
+   					title_conv5d);
+   			QuadCLTCPU.saveImagePlusInDirectory(imp_5d, getModelDirectory());
+   		}
+   		for (int nlev = 0; nlev < pyramid_levels; nlev++) {
    	       	if (save_LoG_pixels) {
    	       		String title_conv2d_lev = getBaseName()+SUFFIX_CONV2D+"-PSF"+d2s(cuasRTUtils.getPsfRadius())+
    	       				"-KR"+d2s(cuasRTUtils.getKernel2dRadius())+"-ALPHA0_"+d2s(alpha0)+"-ALPHAPYR_"+d2s(alpha_pyr)+"-LEV"+nlev;
@@ -339,6 +350,25 @@ public class CuasDetectRT {
    		   					title_conv3d3+"-LEV"+(nlev+1));   // String        title)
    		   			QuadCLTCPU.saveImagePlusInDirectory(imp_3d3, getModelDirectory());
    		   		}
+   		   		// 5D convolution for pyramid level nlev+1
+   		   		int num_5d_lev = Math.max(0, dpixels_3d3_pyramid[nlev+1].length - num_hist_5d + 1);
+   		   		dpixels_5d_pyramid[nlev+1] = new double[num_5d_lev][][][];
+   		   		String[] ts_5d_lev = new String[num_5d_lev];
+   		   		for (int n5d = 0; n5d < num_5d_lev; n5d++) {
+   		   			double[][][] window = new double[num_hist_5d][][];
+   		   			for (int h = 0; h < num_hist_5d; h++) {
+   		   				window[h] = dpixels_3d3_pyramid[nlev+1][n5d + num_hist_5d - 1 - h];
+   		   			}
+   		   			dpixels_5d_pyramid[nlev+1][n5d] = cuasRTUtils.convolve3d(window, null);
+   		   			ts_5d_lev[n5d] = ts_pyramid[nlev+1][n5d + num_hist_5d - 1];
+   		   		}
+   		   		if (save_5d_pixels && num_5d_lev > 0) {
+   		   			ImagePlus imp_5d = cuasRTUtils.showConvKernel5d(
+   		   					dpixels_5d_pyramid[nlev+1],
+   		   					ts_5d_lev,
+   		   					title_conv5d+"-LEV"+(nlev+1));
+   		   			QuadCLTCPU.saveImagePlusInDirectory(imp_5d, getModelDirectory());
+   		   		}
    			}
    		}
    		return null;

src/main/java/com/elphel/imagej/cuas/rt/CuasRTUtils.java

@@ -116,8 +116,11 @@ public class CuasRTUtils {
 	public int get3d3Radius() {
 		return kernel3d3_rad;
 	}
-	
-	
+
+	public int getNumHist() {
+		return kernel5d.length;
+	}
+
 	public double [] getKernel2d() {
 		return kernel2d;
 	}