ij.plugin.filter.GaussianBlur.<init>()方法的使用及代码示例

x33g5p2x  于2022-01-20 转载在 其他  
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本文整理了Java中ij.plugin.filter.GaussianBlur.<init>()方法的一些代码示例，展示了GaussianBlur.<init>()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。GaussianBlur.<init>()方法的具体详情如下：
包路径：ij.plugin.filter.GaussianBlur
类名称：GaussianBlur
方法名：<init>

GaussianBlur.<init>介绍

暂无

代码示例

代码示例来源：origin: stackoverflow.com

importClass(Packages.ij.plugin.filter.GaussianBlur);

var imp = IJ.openImage("http://imagej.nih.gov/ij/images/clown.jpg");
IJ.run(imp, "8-bit", "");

var ip = imp.getProcessor();
var gs = new GaussianBlur();
gs.blurGaussian(ip,20,20,0.01);
imp.show();

代码示例来源：origin: net.imagej/ij

/** 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); 
  }
}

代码示例来源：origin: sc.fiji/TrakEM2_

@Override
public ImageProcessor process(ImageProcessor ip) {
  ij.plugin.filter.GaussianBlur g = new ij.plugin.filter.GaussianBlur();
  g.blurGaussian(ip, sigmaX, sigmaY, accuracy);
  return ip;
}

代码示例来源：origin: imagej/ImageJA

/** 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); 
  }
}

代码示例来源：origin: sc.fiji/bUnwarpJ_

/**
 * Smooth with a Gaussian kernel that represents downsampling at a given
 * scale factor and sourceSigma.
 */
final static public void smoothForScale(
  final ImageProcessor source,
  final float scale,
  final float sourceSigma,
  final float targetSigma )
{
  if ( scale >= 1.0f ) return;
  float s = targetSigma / scale;
  float sigma = ( float )Math.sqrt( s * s - sourceSigma * sourceSigma );
  new GaussianBlur().blurGaussian( source, sigma, sigma, 0.01 );
}

代码示例来源：origin: stackoverflow.com

@Override
public void start(Stage primaryStage) throws Exception {
  Parent root = FXMLLoader.load(getClass().getResource("/views/main.fxml"));
  Scene scene = new Scene(root);
  scene.getStylesheets().add(this.getClass().getResource("/style/main.css").toExternalForm());
  primaryStage.setScene(scene);
  primaryStage.show();
  windowMain = primaryStage;
  root.setEffect(new GaussianBlur());
  loginWindow.display();
  root.setEffect(null);
}

代码示例来源：origin: net.imagej/ij

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;
}

代码示例来源：origin: net.imagej/ij

/** Blurs the image by convolving with a Gaussian function. */
public void blurGaussian(double sigma) {
  resetRoi();
  GaussianBlur gb = new GaussianBlur();
  gb.showProgress(false);
  gb.blurGaussian(this, sigma);
}

代码示例来源：origin: imagej/ImageJA

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;
}

代码示例来源：origin: net.imagej/ij

/** 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();
  Rectangle roi = fp.getRoi();
  for (int y=roi.y; y<roi.y+roi.height; y++)
    for (int x=roi.x, p=width*y+x; x<roi.x+roi.width; x++,p++)
      pixels[p] = (snapshotPixels[p] - weight*pixels[p])/(1f - weight);
}

代码示例来源：origin: imagej/ImageJA

/** Blurs the image by convolving with a Gaussian function. */
public void blurGaussian(double sigma) {
  resetRoi();
  GaussianBlur gb = new GaussianBlur();
  gb.showProgress(false);
  gb.blurGaussian(this, sigma);
}

代码示例来源：origin: imagej/ImageJA

/** 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();
  Rectangle roi = fp.getRoi();
  for (int y=roi.y; y<roi.y+roi.height; y++)
    for (int x=roi.x, p=width*y+x; x<roi.x+roi.width; x++,p++)
      pixels[p] = (snapshotPixels[p] - weight*pixels[p])/(1f - weight);
}

代码示例来源：origin: fiji/Trainable_Segmentation

public ImagePlus call(){

    ImageProcessor ip = originalImage.getProcessor().duplicate();
    GaussianBlur gs = new GaussianBlur();
    //gs.blur(ip, sigma);
    gs.blurGaussian(ip, 0.4 * sigma, 0.4 * sigma,  0.0002);
    return new ImagePlus (availableFeatures[GAUSSIAN] + "_" + sigma, ip);
  }
};

代码示例来源：origin: net.imagej/ij

float[] smooth(float[] a, int n) {
  FloatProcessor fp = new FloatProcessor(n, 1);
  for (int i=0; i<n; i++)
    fp.setf(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] = fp.getf(i, 0);
  return a;
}

代码示例来源：origin: sc.fiji/Trainable_Segmentation

public ImagePlus call(){

    ImageProcessor ip = originalImage.getProcessor().duplicate();
    GaussianBlur gs = new GaussianBlur();
    //gs.blur(ip, sigma);
    gs.blurGaussian(ip, 0.4 * sigma, 0.4 * sigma,  0.0002);
    return new ImagePlus (availableFeatures[GAUSSIAN] + "_" + sigma, ip);
  }
};

代码示例来源：origin: sc.fiji/TrakEM2_

/** WARNING will resize the FloatProcessorT2 source in place, unlike ImageJ standard FloatProcessor class. */
static final private byte[] gaussianBlurResizeInHalf(final FloatProcessorT2 source)
{
  new GaussianBlur().blurFloat( source, SIGMA_2, SIGMA_2, 0.01 );
  source.halfSizeInPlace();
  
  return (byte[])source.convertToByte(false).getPixels(); // no scaling
}

代码示例来源：origin: imagej/ImageJA

float[] smooth(float[] a, int n) {
  FloatProcessor fp = new FloatProcessor(n, 1);
  for (int i=0; i<n; i++)
    fp.setf(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] = fp.getf(i, 0);
  return a;
}

代码示例来源：origin: sc.fiji/Trainable_Segmentation

/**
 * Add Gaussian blur slice to current stack
 * @param sigma Gaussian radius
 */
public void addGaussianBlur(float sigma)
{
  ImageProcessor ip = originalImage.getProcessor().duplicate();
  GaussianBlur gs = new GaussianBlur();
  //gs.blur(ip, sigma);
  gs.blurGaussian(ip, 0.4 * sigma, 0.4 * sigma,  0.0002);
  wholeStack.addSlice(availableFeatures[GAUSSIAN] + "_" + sigma, ip);
}
/**

代码示例来源：origin: fiji/Trainable_Segmentation

/**
 * Add Gaussian blur slice to current stack
 * @param sigma Gaussian radius
 */
public void addGaussianBlur(float sigma)
{
  ImageProcessor ip = originalImage.getProcessor().duplicate();
  GaussianBlur gs = new GaussianBlur();
  //gs.blur(ip, sigma);
  gs.blurGaussian(ip, 0.4 * sigma, 0.4 * sigma,  0.0002);
  wholeStack.addSlice(availableFeatures[GAUSSIAN] + "_" + sigma, ip);
}
/**

代码示例来源：origin: sc.fiji/TrakEM2_

/**
 * Gaussian-downsample to the target dimensions
 * @param ip
 * @return
 */
protected FloatProcessor gaussianDownsampled( final FloatProcessor ip )
{
  loader.releaseToFit( ( (float[])ip.getPixels() ).length * 2 );
  // Gaussian-downsample
  final double sigma = computeSigma( ip.getWidth(), ip.getHeight() );
  Utils.log("Gaussian downsampling. If this is slow, check the number of threads in the plugin preferences.");
  new GaussianBlur().blurFloat( ip, sigma, sigma, 0.0002 );
  ip.setInterpolationMethod( ImageProcessor.NEAREST_NEIGHBOR );
  return (FloatProcessor) ip.resize( ( int ) Math.ceil( finalBox.width * scale ) );
}

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