public void calAutoCorrelation_RingMean( int nRefType) { // crosscorrelation coefficients between pixel valuse and the means and // medians of the pixels located on the cocentric rings with radius up to // m_nRMax m_nRefType = nRefType; int numRings = m_cvRings.size(); calRefPixels(); int r, c; int len = m_cIMSC.m_nTotalSteps + 1; double[] pixels0 = new double[len]; double[] meanr = new double[len]; double[] medianr = new double[len]; int index = 0; Point p; index = 0; while (true) { p = m_cIMSC.getPosition(); pixels0[index] = m_pnPixelsLR[p.y][p.x]; index++; if (m_cIMSC.done()) break; m_cIMSC.move(); } ImageShape shape; Histogram hist = CommonMethods.getDefaultHistogram(m_pnPixelsLR); int y, y0 = 0; int nRef; for (c = 0; c < numRings - 1; c++) { index = 0; m_cIMSC.reset(); y0 = m_cIMSC.getPosition().y; shape = m_cvRings.get(c); while (true) { p = m_cIMSC.getPosition(); nRef = getRefPixel(p); y = p.y; if (y > y0) { IJ.showStatus( "calAutoCorrelation_RingMean: r=" + PrintAssist.ToString(c + 1) + " y=" + PrintAssist.ToString(y)); y0 = y; } CommonMethods.fillHistogram(m_pnPixels, nRef, shape, p, hist); meanr[index] = hist.getMean(); medianr[index] = hist.getPercentileValue(); index++; if (m_cIMSC.done()) break; m_cIMSC.move(); } m_pdAutoCorr_mean[c] = CommonStatisticsMethods.crossCorrelationCoefficient(pixels0, meanr, 0); m_pdAutoCorr_median[c] = CommonStatisticsMethods.crossCorrelationCoefficient(pixels0, medianr, 0); } }
void init() { m_nExcludingType = -1; m_pnPixelsCompensated = new int[h][w]; m_pnPixels = new int[h][w]; m_pnPixelsTemp = new int[h][w]; constructRings(); m_cvHists = new ArrayList(); CommonMethods.getPixelValue(impl, impl.getCurrentSlice(), m_pnPixels); Point p = new Point(0, 0); int pRange[] = new int[2]; CommonMethods.getPixelValueRange_Stack(impl, pRange); int nNumRings = m_cvRings.size(); m_pcMeanSems_Mean = new MeanSem0[nNumRings]; m_pcMeanSems_Median = new MeanSem0[nNumRings]; m_cPixelMeanSems = new MeanSem0(); m_cAreaMeanSems_Mean = new MeanSem0(); m_cAreaMeanSems_Median = new MeanSem0(); Histogram hist; for (int r = 0; r < nNumRings; r++) { hist = new Histogram(); hist.update(0, pRange[0], pRange[1], 1); m_cvHists.add(hist); m_pcMeanSems_Mean[r] = new MeanSem0(); m_pcMeanSems_Median[r] = new MeanSem0(); } m_pdAutoCorr_mean = new double[nNumRings]; m_pdAutoCorr_median = new double[nNumRings]; m_nPercentileDivision = (int) (1. / m_dDeltaPercentile); m_pcRingMeanSems_Mean = new MeanSem0[m_nPercentileDivision][nNumRings]; m_pcRingMeanSems_Median = new MeanSem0[m_nPercentileDivision][nNumRings]; m_cPixelMeanSems_trail = new MeanSem0[m_nPercentileDivision]; m_pnAveRadius = new int[m_nPercentileDivision]; m_pnStamp = new int[h][w]; }
int refinePixelStatitics() { stampIPOs(); int[][] pixelsTemp = m_pnPixels; m_pnPixels = m_pnPixelsCompensated; m_cIMSC.reset(); int len = m_cIMSC.m_nTotalSteps + 1; int i, c, step = 0; Point p = m_cIMSC.getPosition(); int index = 0; ImageShape shape; Histogram hist; double mean, median; int y, y0 = 0; int pixel, nRef; double dsur; int numRings = m_cvRings.size(); while (true) { p = m_cIMSC.getPosition(); y = p.y; if (y > y0) IJ.showStatus( "refinePixelStatistics " + PrintAssist.ToString(y) + "-th line of " + PrintAssist.ToString(h) + " lines!"); index = getPercentileIndex(step); dsur = m_pcRingMeanSems_Mean[index][m_nRMax].mean; ImageShapeHandler.copyElements(m_pnPixelsCompensated, m_pnPixelsTemp, m_cvRings, p); for (i = 0; i < numRings; i++) { pixel = (int) (m_pcRingMeanSems_Mean[index][i].mean - dsur); if (pixel < 1) break; shape = m_cvRings.get(i); shape.setCenter(p); ImageShapeHandler.addValue(m_pnPixelsTemp, shape, pixel); } nRef = (int) ImageShapeHandler.getMean(m_pnPixelsTemp, m_cRefRing, m_pnStamp, m_nExcludingType); CommonMethods.fillHistogram( m_pnPixelsTemp, nRef, m_cvRings.get(numRings - 1), p, m_cvHists.get(numRings - 1), m_pnStamp, m_nExcludingType); CommonMethods.fillHistograms(m_pnPixelsTemp, nRef, m_cvRings, p, m_cvHists); for (i = 0; i < numRings; i++) { hist = m_cvHists.get(i); mean = hist.getMeanSem().mean; median = hist.getPercentileValue(); m_pdRingMean[step][i] = mean; m_pdRingMedian[step][i] = median; } // m_pnPixels_trail[step]=m_pnPixelsTemp[p.y][p.x]-nRef; if (m_cIMSC.done()) break; m_cIMSC.move(); step++; } for (c = 0; c < numRings; c++) { m_pcMeanSems_Median[c] = CommonStatisticsMethods.buildMeanSem(m_pdRingMedian, c); m_pcMeanSems_Mean[c] = CommonStatisticsMethods.buildMeanSem(m_pdRingMean, c); } if (m_bPresetPoints) { len = pixelsOfPresetPoints.size(); int num = len / m_nPercentileDivision; int rI, rF; for (i = 0; i < m_nPercentileDivision; i++) { rI = Math.max(0, (int) ((i - .5) * num)); rF = Math.min(len - 1, (int) ((i + .5) * num)); for (c = 0; c < numRings; c++) { m_pcRingMeanSems_Median[i][c] = CommonStatisticsMethods.buildMeanSem(m_pdRingMedian, rI, rF, 1, c); m_pcRingMeanSems_Mean[i][c] = CommonStatisticsMethods.buildMeanSem(m_pdRingMean, rI, rF, 1, c); } } } m_pnPixels = pixelsTemp; return 1; }
public void calAutoCorrelation( int nRefType) { // computing the cross correlation coefficient between pixel values of points // separated by the radius of rings m_nRefType = nRefType; int numRings = m_cvRings.size(); calRefPixels(); m_cPixelMeanSems = CommonStatisticsMethods.buildMeanSem(m_pnPixelsLR); int len; double mean = m_cPixelMeanSems.mean, sem2 = m_cPixelMeanSems.sem2; double medianMean[] = new double[numRings - 1]; double medianSem2[] = new double[numRings - 1]; double crossProduct[] = new double[numRings - 1]; double numCrossPairs[] = new double[numRings - 1]; double crossProduct_median[] = new double[numRings - 1]; double numCrossPairs_median[] = new double[numRings - 1]; ArrayList<Double> medians[] = new ArrayList[numRings - 1]; int i, j, pixel0; for (i = 0; i < numRings - 1; i++) { crossProduct[i] = 0; numCrossPairs[i] = 0; crossProduct_median[i] = 0; numCrossPairs_median[i] = 0; medianMean[i] = 0; medianSem2[i] = 0; medians[i] = new ArrayList(); } int[][] pixels_LMC = new int[h][w]; ImageShape shape; ArrayList<Point> points = new ArrayList(); ArrayList<Point> scanningTrace = new ArrayList(); double dp, median; Point p0, p; int index = 0, y0 = 0, y; Histogram hist; int nRef, mean1; while (true) { p0 = new Point(m_cIMSC.getPosition()); y = p0.y; scanningTrace.add(p0); pixel0 = m_pnPixelsLR[p0.y][p0.x]; nRef = getRefPixel(p0); dp = pixel0 - mean; CommonMethods.fillHistograms(m_pnPixels, nRef, m_cvRings, p0, m_cvHists); for (i = 0; i < numRings - 1; i++) { shape = m_cvRings.get(i); shape.setCenter(p0); shape.setFrameRanges( new intRange(p0.x, w - 1), new intRange( p0.y, h - 1)); // this is to avoid double counting the pair of points with given distance shape.getInnerPoints(points); shape.setFrameRanges(new intRange(0, w - 1), new intRange(0, h - 1)); len = points.size(); for (j = 0; j < len; j++) { p = points.get(j); crossProduct[i] += dp * (m_pnPixels[p.y][p.x] - nRef - mean); } numCrossPairs[i] += len; numCrossPairs_median[i] += 1; hist = m_cvHists.get(i); median = hist.getPercentileValue(); medianMean[i] += median; medianSem2[i] += median * median; medians[i].add(median); if (y > y0) { IJ.showStatus("computing autocorrelation: " + PrintAssist.ToString(y) + "-th line"); IJ.showProgress(y / h); y0 = y; } } if (m_cIMSC.done()) break; m_cIMSC.move(); index++; } double dAutoCorr_mean, meanMedian, cp; MeanSem0 ms = new MeanSem0(); int num; for (i = 0; i < numRings - 1; i++) { m_pdAutoCorr_mean[i] = crossProduct[i] / (Math.sqrt(sem2 * sem2) * (numCrossPairs[i])); num = medians[i].size(); medianMean[i] /= num; medianSem2[i] /= num; ms.updateMeanSquareSum(num, medianMean[i], medianSem2[i]); meanMedian = ms.mean; cp = 0; for (j = 0; j < num; j++) { p = scanningTrace.get(j); cp += (m_pnPixelsLR[p.y][p.x] - mean) * (medians[i].get(j) - meanMedian); } m_pdAutoCorr_median[i] = cp / (Math.sqrt(sem2 * ms.sem2) * (num)); } }
void calPixelStatistics() { calRefPixels(); int len = m_cIMSC.m_nTotalSteps + 1; int numRings = m_cvRings.size(); m_pdRingMean = new double[len][numRings]; m_pdRingMedian = new double[len][numRings]; int i, c; Point p = m_cIMSC.getPosition(); int index = 0; // ImageShape shape; Histogram hist; double mean, median; int y, y0 = 0; int nRef; while (true) { p = m_cIMSC.getPosition(); y = p.y; if (y > y0) IJ.showStatus( "calPixelStatistics " + PrintAssist.ToString(y) + "-th line of " + PrintAssist.ToString(h) + " lines!"); // m_cRefRing.setCenter(p); nRef = getRefPixel(p); CommonMethods.fillHistograms(m_pnPixels, nRef, m_cvRings, p, m_cvHists); for (i = 0; i <= m_nRMax; i++) { hist = m_cvHists.get(i); mean = hist.getMeanSem().mean; median = hist.getPercentileValue(); m_pdRingMean[index][i] = mean; m_pdRingMedian[index][i] = median; } if (m_cIMSC.done()) break; m_cIMSC.move(); index++; } m_cPixelMeanSems = CommonStatisticsMethods.buildMeanSem(m_pnPixelsLR); // m_cPixelMeanSem_trail=CommonStatisticsMethods.buildMeanSem(m_pnPixels_trail); for (c = 0; c <= m_nRMax; c++) { m_pcMeanSems_Median[c] = CommonStatisticsMethods.buildMeanSem(m_pdRingMedian, c); m_pcMeanSems_Mean[c] = CommonStatisticsMethods.buildMeanSem(m_pdRingMean, c); } if (m_bPresetPoints) { len = pixelsOfPresetPoints.size(); int num = len / m_nPercentileDivision; int rI, rF; for (i = 0; i < m_nPercentileDivision; i++) { rI = Math.max(0, (int) ((i - .5) * num)); rF = Math.min(len - 1, (int) ((i + .5) * num)); // // m_cPixelMeanSems_trail[i]=CommonStatisticsMethods.buildMeanSem(m_pnPixels_trail,rI,rF,1); for (c = 0; c < numRings; c++) { m_pcRingMeanSems_Median[i][c] = CommonStatisticsMethods.buildMeanSem(m_pdRingMedian, rI, rF, 1, c); m_pcRingMeanSems_Mean[i][c] = CommonStatisticsMethods.buildMeanSem(m_pdRingMean, rI, rF, 1, c); } } } }