Examples of ij.plugin.filter.GaussianBlur

ij.plugin.filter.GaussianBlur
This plug-in filter uses convolution with a Gaussian function for smoothing. 'Radius' means the radius of decay to exp(-0.5) ~ 61%, i.e. the standard deviation sigma of the Gaussian (this is the same as in Photoshop, but different from the 'Gaussian Blur' in ImageJ versions before 1.38u, where a value 2.5 times as much had to be entered. - Like all convolution operations in ImageJ, it assumes that out-of-image pixels have a value equal to the nearest edge pixel. This gives higher weight to edge pixels than pixels inside the image, and higher weight to corner pixels than non-corner pixels at the edge. Thus, when smoothing with very high blur radius, the output will be dominated by the edge pixels and especially the corner pixels (in the extreme case, with a blur radius of e.g. 1e20, the image will be raplaced by the average of the four corner pixels). - For increased speed, except for small blur radii, the lines (rows or columns of the image) are downscaled before convolution and upscaled to their original length thereafter. Version 03-Jun-2007 M. Schmid with preview, progressBar stack-aware, snapshot via snapshot flag; restricted range for resetOutOfRoi 20-Feb-2010 S. Saalfeld inner multi-threading

        sharpenFloat((FloatProcessor)ip, sigma, (float)weight);
    }
    
    /** Unsharp Mask filtering of a float image. 'fp' must have a valid snapshot. */
    public void sharpenFloat(FloatProcessor fp, double sigma, float weight) {
        if (gb == null) gb = new GaussianBlur();
        gb.blurGaussian(fp, sigma, sigma, 0.01);
        if (Thread.currentThread().isInterrupted()) return;
        float[] pixels = (float[])fp.getPixels();
        float[] snapshotPixels = (float[])fp.getSnapshotPixels();
        int width = fp.getWidth();

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    /** Since most computing time is spent in GaussianBlur, forward the
     * information about the number of passes to Gaussian Blur. The
     * ProgressBar will be handled by GaussianBlur. */
    public void setNPasses(int nPasses) {
        if (gb == null) gb = new GaussianBlur();
        gb.setNPasses(nPasses); 
    }

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        sharpenFloat((FloatProcessor)ip, sigma, (float)weight);
    }
    
    /** Unsharp Mask filtering of a float image. 'fp' must have a valid snapshot. */
    public void sharpenFloat(FloatProcessor fp, double sigma, float weight) {
        if (gb == null) gb = new GaussianBlur();
        gb.blurGaussian(fp, sigma, sigma, 0.01);
        if (Thread.currentThread().isInterrupted()) return;
        float[] pixels = (float[])fp.getPixels();
        float[] snapshotPixels = (float[])fp.getSnapshotPixels();
        int width = fp.getWidth();

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    /** Since most computing time is spent in GaussianBlur, forward the
     * information about the number of passes to Gaussian Blur. The
     * ProgressBar will be handled by GaussianBlur. */
    public void setNPasses(int nPasses) {
        if (gb == null) gb = new GaussianBlur();
        gb.setNPasses(nPasses); 
    }

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    histogram[stats.mode] = originalModeCount;
    float[] hist = new float[256];
    for (int i=0; i<256; i++)
      hist[i] = stats.histogram[i];
    FloatProcessor fp = new FloatProcessor(256, 1, hist, null);
    GaussianBlur gb = new GaussianBlur();
    gb.blur1Direction(fp, 2.0, 0.01, true, 0);
    float maxCount=0f, sum=0f, mean, count;
    int mode = 0;
    for (int i=0; i<256; i++) {
      count = hist[i];
      sum += count;

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  int[] smooth(int[] a, int n) {
    FloatProcessor fp = new FloatProcessor(n, 1);
    for (int i=0; i<n; i++)
      fp.putPixelValue(i, 0, a[i]);
    GaussianBlur gb = new GaussianBlur();
    gb.blur1Direction(fp, 2.0, 0.01, true, 0);
    for (int i=0; i<n; i++)
      a[i] = (int)Math.round(fp.getPixelValue(i, 0));
    return a;
  }

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Related Classes of ij.plugin.filter.GaussianBlur

ij.gui.GenericDialog

ij.plugin.filter.UnsharpMask

ij.plugin.Selection

ij.process.FloatProcessor

ij.process.ImageProcessor

java.awt.Rectangle

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