java - Java 中的 Perlin 噪声问题

Question

所以我试图生成柏林噪声并将其保存到图像文件中。我已经正确保存了图像，但噪音看起来并​​不像柏林噪音。

这是我的代码：

package com.egs.survivalsim.util;

import java.awt.Color;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;

import javax.imageio.ImageIO;

import com.egs.survivalsim.MainComponent;

public class Noise {

    MainComponent main;

    public double noise(int x,int y){
        x = x + y * 57;
        x = ((x << 13) ^ x);
        double t = (x * (x * x * 15731 + 789221) + 1376312589) & 0x7fffffff;
        return 1 - t * 0.000000000931322574615478515625;
    }

    public double sNoise(int x, int y){
        double corners = (noise(x - 1, y - 1) + noise(x + 1, y - 1) + noise(x - 1, y + 1) + noise(x + 1, y + 1)) * 0.0625;
        double sides = (noise(x - 1, y)  + noise(x + 1, y) + noise(x, y - 1) + noise(x, y + 1))  * 0.125;
        double center = noise(x, y) * 0.25;
        return corners + sides + center;        
    }

    public double lInterpoleLin(double a, double b, double x){
        return a * (1 - x) + b * x;     
    }

    public double lInterpoleCos(double a, double b, double x){
        double ft = x * 3.1415927;
        double f = (1 - Math.cos(ft)) * 0.001;
        return a * (1 - f) + b * f;
    }

    public double iNoise(double x, double y){
        int iX = (int) x;
        int iY = (int) y;
        double dX = x - iX;
        double dY = y - iY;
        double p1 = sNoise(iX, iY);
        double p2 = sNoise(iX + 1, iY);
        double p3 = sNoise(iX, iY + 1);
        double p4 = sNoise(iX + 1, iY + 1);
        double i1 = lInterpoleCos(p1 ,p2 ,dX);
        double i2 = lInterpoleCos(p3, p4, dX);
        return lInterpoleCos(i1, i2, dY);   
    }   

    public double pNoise(double x, double y, double persistence, int octave){
        double result;
        double amplitude = 1;
        int frequence = 1;
        result = 0;
        for(int n = 0; n < octave; n++){
            frequence <<= 1;
            amplitude *= persistence;
            result += iNoise(x * frequence, y * frequence) * amplitude;
        }
        return result;  
    }

    public void startNoise(MainComponent main){
        System.out.println("Generating noise map");
        this.main = main;
        System.out.println("Width: " + main.worldWidth);
        System.out.println("Height: " + main.worldHeight);
        BufferedImage image = new BufferedImage(main.worldWidth, main.worldHeight, BufferedImage.TYPE_INT_RGB);
        for(int y = 0; y < main.worldHeight; y++){
            for(int x = 0; x < main.worldWidth; x++){
                double c = pNoise((double) x - main.worldWidth, (double) y - main.worldHeight, 0.2, 2);

                c *= 128.0;
                c += 127.0;
                if(c > 255.0){
                    c = 255.0;
                }
                if(c < 0.0){
                    c = 0.0;
                }

                int r = (int) c;
                int g = (int) c;
                int b = (int) c;

                if(c>128)
                     r>>=1;
                    if(c>128)
                     b>>=1;


                int color = new Color(r, g, b).getRGB();

                image.setRGB(x, y, color);
                main.noiseArray[x][y] = (int) c;
            }
        }

        File fileImage = new File("noise.png");
        try {
            ImageIO.write(image, "png", fileImage);
        } catch (IOException e) {
            e.printStackTrace();
        }
        System.out.println("Noise map generated");
    }
}

Answer 1

不，确实这看起来有点奇怪。首先，噪音的产生似乎存在问题。其次，我真的不知道您为什么要创建彩色图像。最快的解决方案是查看Ken Perlin的最新出版物并查看他的参考实现。

通过简单的复制和粘贴以及几行额外的 java 代码，您将获得漂亮的图像。

请注意，我真的只是把它砍掉了，这意味着我手动缩放了采样范围，使其看起来不错，而且由于我不知道 Perlin 噪声的值在哪个范围内，所以我只是重新缩放了数组以适应在 [0, 255] 范围内。

在下面的代码中，只有main是重要的。其余部分是从 Perlin 复制的。

import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;

public class Noise {

  static final int p[] = new int[512], permutation[] = {151, 160, 137, 91, 90, 15,
    131, 13, 201, 95, 96, 53, 194, 233, 7, 225, 140, 36, 103, 30, 69, 142, 8, 99, 37, 240, 21, 10, 23,
    190, 6, 148, 247, 120, 234, 75, 0, 26, 197, 62, 94, 252, 219, 203, 117, 35, 11, 32, 57, 177, 33,
    88, 237, 149, 56, 87, 174, 20, 125, 136, 171, 168, 68, 175, 74, 165, 71, 134, 139, 48, 27, 166,
    77, 146, 158, 231, 83, 111, 229, 122, 60, 211, 133, 230, 220, 105, 92, 41, 55, 46, 245, 40, 244,
    102, 143, 54, 65, 25, 63, 161, 1, 216, 80, 73, 209, 76, 132, 187, 208, 89, 18, 169, 200, 196,
    135, 130, 116, 188, 159, 86, 164, 100, 109, 198, 173, 186, 3, 64, 52, 217, 226, 250, 124, 123,
    5, 202, 38, 147, 118, 126, 255, 82, 85, 212, 207, 206, 59, 227, 47, 16, 58, 17, 182, 189, 28, 42,
    223, 183, 170, 213, 119, 248, 152, 2, 44, 154, 163, 70, 221, 153, 101, 155, 167, 43, 172, 9,
    129, 22, 39, 253, 19, 98, 108, 110, 79, 113, 224, 232, 178, 185, 112, 104, 218, 246, 97, 228,
    251, 34, 242, 193, 238, 210, 144, 12, 191, 179, 162, 241, 81, 51, 145, 235, 249, 14, 239, 107,
    49, 192, 214, 31, 181, 199, 106, 157, 184, 84, 204, 176, 115, 121, 50, 45, 127, 4, 150, 254,
    138, 236, 205, 93, 222, 114, 67, 29, 24, 72, 243, 141, 128, 195, 78, 66, 215, 61, 156, 180
  };

  static {
    for (int i = 0; i < 256; i++) p[256 + i] = p[i] = permutation[i];
  }

  static public double noise(double x, double y, double z) {
    int X = (int) Math.floor(x) & 255,                  // FIND UNIT CUBE THAT
      Y = (int) Math.floor(y) & 255,                  // CONTAINS POINT.
      Z = (int) Math.floor(z) & 255;
    x -= Math.floor(x);                                // FIND RELATIVE X,Y,Z
    y -= Math.floor(y);                                // OF POINT IN CUBE.
    z -= Math.floor(z);
    double u = fade(x),                                // COMPUTE FADE CURVES
      v = fade(y),                                // FOR EACH OF X,Y,Z.
      w = fade(z);
    int A = p[X] + Y, AA = p[A] + Z, AB = p[A + 1] + Z,      // HASH COORDINATES OF
      B = p[X + 1] + Y, BA = p[B] + Z, BB = p[B + 1] + Z;      // THE 8 CUBE CORNERS,

    return lerp(w, lerp(v, lerp(u, grad(p[AA], x, y, z),  // AND ADD
      grad(p[BA], x - 1, y, z)), // BLENDED
      lerp(u, grad(p[AB], x, y - 1, z),  // RESULTS
        grad(p[BB], x - 1, y - 1, z))),// FROM  8
      lerp(v, lerp(u, grad(p[AA + 1], x, y, z - 1),  // CORNERS
        grad(p[BA + 1], x - 1, y, z - 1)), // OF CUBE
        lerp(u, grad(p[AB + 1], x, y - 1, z - 1),
          grad(p[BB + 1], x - 1, y - 1, z - 1))));
  }

  static double fade(double t) {
    return t * t * t * (t * (t * 6 - 15) + 10);
  }

  static double lerp(double t, double a, double b) {
    return a + t * (b - a);
  }

  static double grad(int hash, double x, double y, double z) {
    int h = hash & 15;                      // CONVERT LO 4 BITS OF HASH CODE
    double u = h < 8 ? x : y,                 // INTO 12 GRADIENT DIRECTIONS.
      v = h < 4 ? y : h == 12 || h == 14 ? x : z;
    return ((h & 1) == 0 ? u : -u) + ((h & 2) == 0 ? v : -v);
  }

  public static void main(String[] args) {
    final int WIDTH = 2 * 256, HEIGHT = 256;

    double[] data = new double[WIDTH * HEIGHT];
    int count = 0;

    for (int y = 0; y < HEIGHT; y++) {
      for (int x = 0; x < WIDTH; x++) {
        data[count++] = PerlinNoise.noise(20.0 * x / WIDTH, 10.0 * y / HEIGHT, 0);
      }
    }

    double minValue = data[0], maxValue = data[0];
    for (int i = 0; i < data.length; i++) {
      minValue = Math.min(data[i], minValue);
      maxValue = Math.max(data[i], maxValue);
    }

    int[] pixelData = new int[WIDTH * HEIGHT];
    for (int i = 0; i < data.length; i++) {
      pixelData[i] = (int) (255 * (data[i] - minValue) / (maxValue - minValue));
    }

    BufferedImage img = new BufferedImage(WIDTH, HEIGHT, BufferedImage.TYPE_BYTE_GRAY);
    img.getRaster().setPixels(0, 0, WIDTH, HEIGHT, pixelData);

    File output = new File("image.jpg");
    try {
      ImageIO.write(img, "jpg", output);
    } catch (IOException e) {
      e.printStackTrace();
    }
  }
}