コード例 #1
0
 int calCompensatedPixels() {
   int numRings = m_cvRings.size();
   CommonStatisticsMethods.copyArray(m_pnPixels, m_pnPixelsCompensated);
   CommonMethods.displayPixels(m_pnPixelsCompensated, "before compensation", impl.getType());
   m_cIMSC.reset();
   Point pt;
   int index, step = 0, pixel, i, r0;
   double dm, dsur;
   ImageShape shape;
   while (true) {
     pt = m_cIMSC.getPosition();
     index = getPercentileIndex(step);
     dsur = m_pcRingMeanSems_Mean[index][m_nRMax].mean;
     r0 = m_pnAveRadius[index];
     //
     // m_pnPixelsCompensated[pt.y][pt.x]-=(int)(m_cPixelMeanSems_trail[index].mean-dsur);
     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(pt);
       ImageShapeHandler.addValue(m_pnPixelsCompensated, shape, -pixel);
     }
     if (m_cIMSC.done()) break;
     m_cIMSC.move();
     step++;
   }
   CommonMethods.displayPixels(m_pnPixelsCompensated, "after compensation", impl.getType());
   return 1;
 }
コード例 #2
0
 void stampIPOs() {
   calAveRadius();
   int i, j;
   for (i = 0; i < h; i++) {
     for (j = 0; j < w; j++) {
       m_pnStamp[i][j] = 0;
     }
   }
   int numRings = m_cvRings.size();
   m_cIMSC.reset();
   Point pt;
   int index, step = 0, r0;
   ImageShape shape;
   while (true) {
     pt = m_cIMSC.getPosition();
     index = getPercentileIndex(step);
     r0 = m_pnAveRadius[index];
     for (i = 0; i <= r0; i++) {
       shape = m_cvRings.get(i);
       shape.setCenter(pt);
       ImageShapeHandler.setValue(m_pnStamp, shape, m_nExcludingType);
     }
     if (m_cIMSC.done()) break;
     m_cIMSC.move();
     step++;
   }
 }
コード例 #3
0
  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;
  }
コード例 #4
0
  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));
    }
  }