Rewriting correlation processing to handle diagonal and multi-baseline (fba24b20) · Commits · Elphel / imagej-elphel

src/main/java/Correlation2d.java

0 → 100644

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src/main/java/DttRad2.java

+61 −0

Original line number	Diff line number	Diff line
		@@ -432,6 +432,66 @@ public class DttRad2 {
		}
		}

		/**
		* Unfolds 2d correlation tile in pixel domain
		* @param qdata 4-quadrant result of 2cd DCT2
		* @param transform_size DCT transformation size
		* @return packed array [(2transform_size-1) (2*transform_size-1)]
		*/

		public double [] corr_unfold_tile(
		double [][] qdata, // [4][transform_size*transform_size] data after DCT2 (pixel domain)
		int transform_size
		)
		{
		int corr_pixsize = transform_size * 2 - 1;
		double corr_pixscale = 0.25;
		double [] rslt = new double [corr_pixsize*corr_pixsize];
		rslt[corr_pixsizetransform_size - transform_size] = corr_pixscale qdata[0][0]; // center
		for (int j = 1; j < transform_size; j++) { // for i == 0
		rslt[corr_pixsizetransform_size - transform_size + j] = corr_pixscale (qdata[0][j] + qdata[1][j-1]);
		rslt[corr_pixsizetransform_size - transform_size - j] = corr_pixscale (qdata[0][j] - qdata[1][j-1]);
		}
		for (int i = 1; i < transform_size; i++) {
		rslt[corr_pixsize*(transform_size + i) - transform_size] =
		corr_pixscale * (qdata[0][itransform_size] + qdata[2][(i-1)transform_size]);
		rslt[corr_pixsize*(transform_size - i) - transform_size] =
		corr_pixscale * (qdata[0][itransform_size] - qdata[2][(i-1)transform_size]);
		for (int j = 1; j < transform_size; j++) {
		rslt[corr_pixsize*(transform_size + i) - transform_size + j] =
		corr_pixscale * (qdata[0][i* transform_size + j] +
		qdata[1][i* transform_size + j - 1] +
		qdata[2][(i-1)*transform_size + j] +
		qdata[3][(i-1)*transform_size + j - 1]);

		rslt[corr_pixsize*(transform_size + i) - transform_size - j] =
		corr_pixscale * ( qdata[0][i* transform_size + j] +
		-qdata[1][i* transform_size + j - 1] +
		qdata[2][(i-1)*transform_size + j] +
		-qdata[3][(i-1)*transform_size + j - 1]);
		rslt[corr_pixsize*(transform_size - i) - transform_size + j] =
		corr_pixscale * (qdata[0][i* transform_size + j] +
		qdata[1][i* transform_size + j - 1] +
		-qdata[2][(i-1)*transform_size + j] +
		-qdata[3][(i-1)*transform_size + j - 1]);
		rslt[corr_pixsize*(transform_size - i) - transform_size - j] =
		corr_pixscale * (qdata[0][i* transform_size + j] +
		-qdata[1][i* transform_size + j - 1] +
		-qdata[2][(i-1)*transform_size + j] +
		qdata[3][(i-1)*transform_size + j - 1]);
		}
		}


		return rslt;

		}






		public double [] dttt_iv(double [] x){
		return dttt_iv(x, 0, 1 << (ilog2(x.length)/2));
		}
		@@ -1085,4 +1145,5 @@ public class DttRad2 {
		}



		}

src/main/java/EyesisCorrectionParameters.java

+3 −3

Original line number	Diff line number	Diff line
		@@ -2350,13 +2350,13 @@ public class EyesisCorrectionParameters {
		public double corr_red = 0.5; // Red to green correlation weight
		public double corr_blue = 0.2; // Blue to green correlation weight
		public boolean corr_normalize = false; // normalize each correlation tile by rms
		public double min_corr = 0.001; // minimal correlation value to consider valid
		public double min_corr = 0.02; // minimal correlation value to consider valid
		public double min_corr_normalized = 2.0; // minimal correlation value to consider valid when normalizing correlation results
		public double max_corr_sigma = 1.5; // weights of points around global max to find fractional
		public double max_corr_sigma = 1.2; // weights of points around global max to find fractional
		// pixel location by quadratic approximation
		public double corr_r2_offset = 0.0; // 0.0 - for compatibility with old, normally should be 2.0 (or 1.0)

		public double max_corr_radius = 3.5; // maximal distance from int max to consider
		public double max_corr_radius = 3.9; // maximal distance from int max to consider

		// public int enhortho_width = 2; // reduce weight of center correlation pixels from center (0 - none, 1 - center, 2 +/-1 from center)
		// public double enhortho_scale = 0.0; // 0.2; // multiply center correlation pixels (inside enhortho_width)

src/main/java/ImageDtt.java

+137 −8

Original line number	Diff line number	Diff line
		@@ -82,10 +82,16 @@ public class ImageDtt {
		static int DBG10_INDEX = 27; // index of dbg3 data (poly 3)
		static int DBG11_INDEX = 28; // index of dbg3 data (poly 3)
		static int DBG12_INDEX = 29; // index of dbg3 data (poly 3)
		static int DBG13_INDEX = 30; // index of dbg3 data (poly 3)
		static int DBG14_INDEX = 31; // index of dbg3 data (poly 3)
		static int DBG15_INDEX = 32; // index of dbg3 data (poly 3)
		static int DBG16_INDEX = 33; // index of dbg3 data (poly 3)
		static int DBG17_INDEX = 34; // index of dbg3 data (poly 3)
		static int DBG18_INDEX = 35; // index of dbg3 data (poly 3)
		static String [] DISPARITY_TITLES = {
		"int_disp","int_y_disp","cm_disp","cm_y_disp","hor_disp","hor_strength","vert_disp","vert_strength",
		"poly_disp", "poly_y_disp", "strength_disp", "vary_disp","diff0","diff1","diff2","diff3","overexp",
		"dbg0","dbg1","dbg2","dbg3","dbg4","dbg5","dbg6","dbg7","dbg8","dbg9","dbg10","dbg11","dbg12"};
		"dbg0","dbg1","dbg2","dbg3","dbg4","dbg5","dbg6","dbg7","dbg8","dbg9","dbg10","dbg11","dbg12","dbg13","dbg14","dbg15","dbg16","dbg17","dbg18"};

		static int TCORR_COMBO_RSLT = 0; // normal combined correlation from all selected pairs (mult/sum)
		static int TCORR_COMBO_SUM = 1; // sum of channel correlations from all selected pairs
		@@ -1409,9 +1415,9 @@ public class ImageDtt {
		final double corr_blue,
		final double corr_sigma,
		final boolean corr_normalize, // normalize correlation results by rms
		final double min_corr, // 0.0001; // minimal correlation value to consider valid
		final double max_corr_sigma, // 1.5; // weights of points around global max to find fractional
		final double max_corr_radius, // 3.5;
		final double min_corr, // 0.02; // minimal correlation value to consider valid
		final double max_corr_sigma, // 1.2; // weights of points around global max to find fractional
		final double max_corr_radius, // 3.9;

		// final int enhortho_width, // 2; // reduce weight of center correlation pixels from center (0 - none, 1 - center, 2 +/-1 from center)
		// final double enhortho_scale, // 0.2; // multiply center correlation pixels (inside enhortho_width)
		@@ -1627,6 +1633,33 @@ public class ImageDtt {
		}
		}
		*/
		// Correlation2d corr2d = new Correlation2d(transform_size);

		final double [] corr_wndy = (new Correlation2d(transform_size)).halfFlatTopWindow(
		imgdtt_params.corr_wndy_size, // int ihwidth,
		imgdtt_params.corr_wndy_hwidth, // double hwidth,
		imgdtt_params.corr_wndy_blur, // double blur,
		true, // boolean normalize,
		1.0); // double scale);

		final double [] corr_wndx = (new Correlation2d(transform_size)).halfFlatTopWindow(
		imgdtt_params.corr_wndx_size, // int ihwidth,
		imgdtt_params.corr_wndx_hwidth, // double hwidth,
		imgdtt_params.corr_wndx_blur, // double blur,
		true, // boolean normalize,
		2.0); // double scale);
		if (globalDebugLevel > -1) {
		System.out.println("\ncorr_wndy:");
		for (int i = 0; i <corr_wndy.length; i++) {
		System.out.println(i+": "+corr_wndy[i]);
		}
		System.out.println("\ncorr_wnxy:");
		for (int i = 0; i <corr_wndx.length; i++) {
		System.out.println(i+": "+corr_wndx[i]);
		}
		}


		final Matrix [] corr_rots = geometryCorrection.getCorrVector().getRotMatrices(); // get array of per-sensor rotation matrices
		for (int ithread = 0; ithread < threads.length; ithread++) {
		threads[ithread] = new Thread() {
		@@ -2007,7 +2040,8 @@ public class ImageDtt {
		}
		// convert from 4 quadrants to 15x15 centered tiles (each color or only composite)
		for (int chn = firstColor; chn <= numcol; chn++){
		tcorr_partial[pair][chn] = corr_unfold_tile(
		// tcorr_partial[pair][chn] = corr_unfold_tile(
		tcorr_partial[pair][chn] = dtt.corr_unfold_tile(
		tcorr_tpartial[pair][chn],
		transform_size);
		}
		@@ -2244,14 +2278,14 @@ public class ImageDtt {
		corr_size, // int data_size,
		imgdtt_params.ortho_nsamples, // int num_samples, // number of samples to keep (5?)
		imgdtt_params.ortho_vasw_pwr, // double value_as_weight, // use positive value as sample weight
		(globalDebugLevel > -2) && (tileX == debug_tileX) && (tileY == debug_tileY)); // debugMax);
		false); //(globalDebugLevel > -2) && (tileX == debug_tileX) && (tileY == debug_tileY)); // debugMax);
		corr_max_ortho[1] = getMaxXSOrtho2( // get fractional center using a quadratic polynomial
		tcorr_combo[TCORR_COMBO_VERT],// double [] data, // [data_size * data_size]
		ortho_weights, // double [] enhortho_scales, // [data_size]
		corr_size, // int data_size,
		imgdtt_params.ortho_nsamples, // int num_samples, // number of samples to keep (5?)
		imgdtt_params.ortho_vasw_pwr, // double value_as_weight, // use positive value as sample weight
		(globalDebugLevel > -2) && (tileX == debug_tileX) && (tileY == debug_tileY)); // debugMax);
		false); //(globalDebugLevel > -2) && (tileX == debug_tileX) && (tileY == debug_tileY)); // debugMax);
		// (globalDebugLevel > 0) && (tileX == debug_tileX) && (tileY == debug_tileY)); // debugMax);
		// disparity_map[DISPARITY_INDEX_HOR][tIndex] = transform_size - 1 - corr_max_XS_hor[0];
		// disparity_map[DISPARITY_INDEX_HOR_STRENGTH][tIndex] = corr_max_XS_hor[1];
		@@ -2354,6 +2388,100 @@ public class ImageDtt {
		}
		// use poly only if half-width y < limit (now it is ~2.0 for good corr)

		// test new correlations
		if (disparity_map[DBG12_INDEX] != null) {
		Correlation2d corr2d = new Correlation2d(transform_size);
		// recalculate correlations
		double [][] corrs = corr2d.correlateCompositeFD(
		clt_data, // double [][][][][][] clt_data,
		tileX, // int tileX,
		tileY, // int tileY,
		0x3f, // int pairs_mask,
		filter, // double [] lpf,
		col_weights, // double [] col_weights,
		corr_fat_zero);// double fat_zero)

		double [][] strips = corr2d.scaleRotateInterpoateCorrelations(
		corrs, // double [][] correlations,
		0x3f, // int pairs_mask,
		imgdtt_params.corr_strip_hight, //); // int hwidth);
		((globalDebugLevel > -2) && (tileX == debug_tileX) && (tileY == debug_tileY))?0x3f:0); // debugMax);

		double [] strip_ortho = corr2d.combineInterpolatedCorrelations(
		strips, // double [][] strips,
		0x0f, // int pairs_mask,
		imgdtt_params.corr_offset); // double offset);

		double [] strip_diag = corr2d.combineInterpolatedCorrelations(
		strips, // double [][] strips,
		0x30, // int pairs_mask,
		imgdtt_params.corr_offset); // double offset);

		double [] strip_all = corr2d.combineInterpolatedCorrelations(
		strips, // double [][] strips,
		0x3f, // int pairs_mask,
		imgdtt_params.corr_offset); // double offset);

		double [] strip_combo = corr2d.combineInterpolatedCorrelations(
		strips, // double [][] strips,
		imgdtt_params.dbg_pair_mask, // int pairs_mask,
		imgdtt_params.corr_offset); // double offset);

		// reuse clt_corr_partial,// [tilesY][tilesX][quad]color][(2transform_size-1)(2*transform_size-1)] // if null - will not calculate
		if (clt_corr_partial != null) {
		clt_corr_partial[tileY][tileX][0][0] = corrs[0]; // 1
		clt_corr_partial[tileY][tileX][0][1] = corrs[1]; // 2
		clt_corr_partial[tileY][tileX][0][2] = corrs[2]; // 3
		clt_corr_partial[tileY][tileX][0][3] = corrs[3]; // 4
		clt_corr_partial[tileY][tileX][1][0] = corrs[4]; // 5
		clt_corr_partial[tileY][tileX][1][1] = corrs[5]; // 6
		clt_corr_partial[tileY][tileX][1][2] = corr2d.debugStrip(strips[0]); // 7
		clt_corr_partial[tileY][tileX][1][3] = corr2d.debugStrip(strips[1]); // 8
		clt_corr_partial[tileY][tileX][2][0] = corr2d.debugStrip(strips[2]); // 9
		clt_corr_partial[tileY][tileX][2][1] = corr2d.debugStrip(strips[3]); // 10
		clt_corr_partial[tileY][tileX][2][2] = corr2d.debugStrip(strips[4]); // 11
		clt_corr_partial[tileY][tileX][2][3] = corr2d.debugStrip(strips[5]); // 12
		clt_corr_partial[tileY][tileX][3][0] = corr2d.debugStrip(strip_ortho); // 13
		clt_corr_partial[tileY][tileX][3][1] = corr2d.debugStrip(strip_diag); // 14
		clt_corr_partial[tileY][tileX][3][2] = corr2d.debugStrip(strip_all); // 15
		clt_corr_partial[tileY][tileX][3][3] = corr2d.debugStrip2(strip_combo); // 16
		}
		if ((globalDebugLevel > -2) && (tileX == debug_tileX) && (tileY == debug_tileY)) {
		System.out.println(String.format("tileX=%d, tileY=%d, dbg_pair_mask= 0x%x,corr_offset = %8.5f",
		debug_tileX,debug_tileY,imgdtt_params.dbg_pair_mask, imgdtt_params.corr_offset ));
		}
		// find integer correlation center, relative to the center
		int [] ixy = corr2d.getMaxXYInt( // find integer pair or null if below threshold
		strip_combo, // double [] data, // [data_size * data_size]
		true, // boolean axis_only,
		imgdtt_params.min_corr, // double minMax, // minimal value to consider (at integer location, not interpolated)
		((globalDebugLevel > -2) && (tileX == debug_tileX) && (tileY == debug_tileY))); // boolean debug);
		double [] corr_stat = null;
		if (ixy != null) {
		corr_stat = corr2d.getMaxXCm( // get fractional center as a "center of mass" inside circle/square from the integer max
		strip_combo, // double [] data, // [data_size * data_size]
		ixy[0], // int ixcenter, // integer center x
		corr_wndy, // double [] window_y, // (half) window function in y-direction(perpendicular to disparity: for row0 ==1
		corr_wndx, // double [] window_x, // half of a window function in x (disparity) direction
		((globalDebugLevel > -2) && (tileX == debug_tileX) && (tileY == debug_tileY))); // boolean debug);
		} else {
		corr_stat = new double[3];
		for (int i = 0; i < corr_stat.length; i++) corr_stat[i] = Double.NaN;
		}
		if (disparity_map[DBG18_INDEX] != null) {
		disparity_map[DBG13_INDEX][tIndex] = -corr_stat[0]; // disparity is negative X
		disparity_map[DBG14_INDEX][tIndex] = corr_stat[2]; // half-width
		disparity_map[DBG15_INDEX][tIndex] = corr_stat[1]/corr_stat[2]; // height?
		disparity_map[DBG16_INDEX][tIndex] = corr_stat[1]; // weight
		if (ixy != null) {
		disparity_map[DBG17_INDEX][tIndex] = strip_combo[ixy[0]+transform_size-1];
		disparity_map[DBG18_INDEX][tIndex] = -ixy[0];
		}else {
		disparity_map[DBG17_INDEX][tIndex] = Double.NaN;
		disparity_map[DBG18_INDEX][tIndex] = Double.NaN;
		}
		}
		}

		if (imgdtt_params.mix_corr_poly) { // regardless of debug
		// apply
		@@ -3943,6 +4071,7 @@ public class ImageDtt {
		return rslt;
		}

		/*
		private double [] corr_unfold_tile(
		double [][] qdata, // [4][transform_size*transform_size] data after DCT2 (pixel domain)
		int transform_size
		@@ -3991,7 +4120,7 @@ public class ImageDtt {

		}


		*/
		// extract correlation result in linescan order (for visualization)
		public double [] corr_dbg(
		final double [][][] corr_data,

src/main/java/ImageDttParameters.java

+138 −29

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