图像处理之添加高斯与泊松噪声

package com.gloomyfish.filter.study;
 
import java.awt.image.BufferedImage;
import java.util.Random;
 
public class NoiseAdditionFilter extends AbstractBufferedImageOp {
  public final static double MEAN_FACTOR = 2.0;
  public final static int POISSON_NOISE_TYPE = 2;
  public final static int GAUSSION_NOISE_TYPE = 1;
  private double _mNoiseFactor = 25;
  private int _mNoiseType = POISSON_NOISE_TYPE;
  
  public NoiseAdditionFilter() {
    System.out.println("Adding Poisson/Gaussion Noise");
  }
  
  public void setNoise(double power) {
    this._mNoiseFactor = power;
  }
  
  public void setNoiseType(int type) {
    this._mNoiseType = type;
  }
  
  @Override
  public BufferedImage filter(BufferedImage src, BufferedImage dest) {
    int width = src.getWidth();
        int height = src.getHeight();
        Random random = new Random();
        if ( dest == null )
            dest = createCompatibleDestImage( src, null );
 
        int[] inPixels = new int[width*height];
        int[] outPixels = new int[width*height];
        getRGB( src, 0, 0, width, height, inPixels );
        int index = 0;
        for(int row=0; row<height; row++) {
          int ta = 0, tr = 0, tg = 0, tb = 0;
          for(int col=0; col<width; col++) {
            index = row * width + col;
            ta = (inPixels[index] >> 24) & 0xff;
                tr = (inPixels[index] >> 16) & 0xff;
                tg = (inPixels[index] >> 8) & 0xff;
                tb = inPixels[index] & 0xff;
                if(_mNoiseType == POISSON_NOISE_TYPE) {
                  tr = clamp(addPNoise(tr, random));
                  tg = clamp(addPNoise(tg, random));
                  tb = clamp(addPNoise(tb, random));
                } else if(_mNoiseType == GAUSSION_NOISE_TYPE) {
                  tr = clamp(addGNoise(tr, random));
                  tg = clamp(addGNoise(tg, random));
                  tb = clamp(addGNoise(tb, random));
                }
                outPixels[index] = (ta << 24) | (tr << 16) | (tg << 8) | tb;
          }
        }
 
        setRGB( dest, 0, 0, width, height, outPixels );
        return dest;
  }
  
  private int addGNoise(int tr, Random random) {
    int v, ran;
    boolean inRange = false;
    do {
      ran = (int)Math.round(random.nextGaussian()*_mNoiseFactor);
      v = tr + ran;
      // check whether it is valid single channel value
      inRange = (v>=0 && v<=255); 
      if (inRange) tr = v;
    } while (!inRange);
    return tr; 
  }
 
  public static int clamp(int p) {
    return p > 255 ? 255 : (p < 0 ? 0 : p);
  }
  
  private int addPNoise(int pixel, Random random) {
    // init:
    double L = Math.exp(-_mNoiseFactor * MEAN_FACTOR);
    int k = 0;
    double p = 1;
    do {
      k++;
      // Generate uniform random number u in [0,1] and let p ← p × u.
      p *= random.nextDouble();
    } while (p >= L);
    double retValue = Math.max((pixel + (k - 1) / MEAN_FACTOR - _mNoiseFactor), 0);
    return (int)retValue;
  }
 
}