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c# - 二维柏林噪声

转载 作者:可可西里 更新时间:2023-11-01 07:54:08 26 4
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我已经完全掌握了 3D 柏林噪声的艺术,现在我正在尝试将我的相同实现用于 2D 算法。问题似乎在于选择我的渐变方向。在 3D 中,我在均匀分布的方向上使用了 16 个渐变,效果很好。在 2D 中,我想我会使用 8 个渐变。上、下、左、右、四个对角线方向。

这是我得到的:

enter image description here

噪声的总体外观总是正确的,但正方形的边缘并不完全匹配。我也尝试过使用其他渐变或更少的渐变,但得到了类似的结果。在另一个示例中,您可以看到边缘有时会匹配并且该区域的结果很好 -

enter image description here

当我不使用渐变而只是在 4 个角的每个角随机选取的值之间进行插值时,我得到了正确的结果,这让我认为是渐变部分搞砸了。

这是我的代码:

//8 different gradient directions
private Point[] grads = new Point[] {
new Point(0, 1), new Point(1, 1), new Point(1, 0), new Point(1, -1),
new Point(0, -1), new Point(-1, -1), new Point(-1, 0), new Point(-1, 1),};

//takes the dot product of a gradient and (x, y)
private float dot2D(int i, float x, float y)
{
return
grads[i].X * x + grads[i].Y * y;
}

public float Noise2D(float x, float y)
{
int
ix = (int)(x),
iy = (int)(y);

x = x - ix;
y = y - iy;

float
fx = fade(x),
fy = fade(y);

ix &= 255;
iy &= 255;

// here is where i get the index to look up in the list of
// different gradients.
// hashTable is my array of 0-255 in random order
int
g00 = hashTable[ix + hashTable[iy ]],
g10 = hashTable[ix + 1 + hashTable[iy ]],
g01 = hashTable[ix + hashTable[iy + 1]],
g11 = hashTable[ix + 1 + hashTable[iy + 1]];

// this takes the dot product to find the values to interpolate between
float
n00 = dot2D(g00 & 7, x, y),
n10 = dot2D(g10 & 7, x, y),
n01 = dot2D(g01 & 7, x, y),
n11 = dot2D(g11 & 7, x, y);

// lerp() is just normal linear interpolation
float
y1 = lerp(fx, n00, n10),
y2 = lerp(fx, n01, n11);
return
lerp(fy, y1, y2);
}

最佳答案

我有点匆忙,但这可能会有帮助。我将 Perlin 的引用实现改编为 C#。对于 2D,只需使用具有固定 z 参数的 3D Noise() 函数。 (public static float Noise(float x, float y, float z) 接近类(class)末尾。)

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using Microsoft.Xna.Framework;
using System.Diagnostics;

namespace GoEngine.Content.Entities
{
public class NoiseMaker
{
/// adapted from http://cs.nyu.edu/~perlin/noise/
// JAVA REFERENCE IMPLEMENTATION OF IMPROVED NOISE - COPYRIGHT 2002 KEN PERLIN.

private static int[] p = new int[512];
private static int[] 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 NoiseMaker()
{
CalculateP();
}

private static int _octaves;
private static int _halfLength = 256;

public static void SetOctaves(int octaves)
{
_octaves = octaves;

var len = (int)Math.Pow(2, octaves);

permutation = new int[len];

Reseed();
}

private static void CalculateP()
{
p = new int[permutation.Length * 2];
_halfLength = permutation.Length;

for (int i = 0; i < permutation.Length; i++)
p[permutation.Length + i] = p[i] = permutation[i];
}

public static void Reseed()
{
var random = new Random();
var perm = Enumerable.Range(0, permutation.Length).ToArray();

for (var i = 0; i < perm.Length; i++)
{
var swapIndex = random.Next(perm.Length);

var t = perm[i];

perm[i] = perm[swapIndex];

perm[swapIndex] = t;
}

permutation = perm;

CalculateP();

}

public static float Noise(Vector3 position, int octaves, ref float min, ref float max)
{
return Noise(position.X, position.Y, position.Z, octaves, ref min, ref max);
}

public static float Noise(float x, float y, float z, int octaves, ref float min, ref float max)
{

var perlin = 0f;
var octave = 1;

for (var i = 0; i < octaves; i++)
{
var noise = Noise(x * octave, y * octave, z * octave);

perlin += noise / octave;

octave *= 2;
}

perlin = Math.Abs((float)Math.Pow(perlin,2));
max = Math.Max(perlin, max);
min = Math.Min(perlin, min);

//perlin = 1f - 2 * perlin;

return perlin;
}

public static float Noise(float x, float y, float z)
{
int X = (int)Math.Floor(x) % _halfLength;
int Y = (int)Math.Floor(y) % _halfLength;
int Z = (int)Math.Floor(z) % _halfLength;

if (X < 0)
X += _halfLength;

if (Y < 0)
Y += _halfLength;

if (Z < 0)
Z += _halfLength;

x -= (int)Math.Floor(x);
y -= (int)Math.Floor(y);
z -= (int)Math.Floor(z);

var u = Fade(x);
var v = Fade(y);
var 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 MathHelper.Lerp(
MathHelper.Lerp(
MathHelper.Lerp(
Grad(p[AA], x, y, z) // AND ADD
,
Grad(p[BA], x - 1, y, z) // BLENDED
,
u
)
,
MathHelper.Lerp(
Grad(p[AB], x, y - 1, z) // RESULTS
,
Grad(p[BB], x - 1, y - 1, z)
,
u
)
,
v
)
,
MathHelper.Lerp(
MathHelper.Lerp(
Grad(p[AA + 1], x, y, z - 1) // CORNERS
,
Grad(p[BA + 1], x - 1, y, z - 1) // OF CUBE
,
u
)
,
MathHelper.Lerp(
Grad(p[AB + 1], x, y - 1, z - 1)
,
Grad(p[BB + 1], x - 1, y - 1, z - 1)
,
u
)
,
v
)
,
w
);

}

static float Fade(float t) { return t * t * t * (t * (t * 6 - 15) + 10); }

static float Grad(int hash, float x, float y, float z)
{
int h = hash & 15; // CONVERT LO 4 BITS OF HASH CODE

float 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);
}

}
}

更新

好的,我设法创建了一个有效的 2D 版本。这是类(class):

/// implements improved Perlin noise in 2D. 
/// Transcribed from http://www.siafoo.net/snippet/144?nolinenos#perlin2003
/// </summary>
public static class Noise2d
{
private static Random _random = new Random();
private static int[] _permutation;

private static Vector2[] _gradients;

static Noise2d()
{
CalculatePermutation(out _permutation);
CalculateGradients(out _gradients);
}

private static void CalculatePermutation(out int[] p)
{
p = Enumerable.Range(0, 256).ToArray();

/// shuffle the array
for (var i = 0; i < p.Length; i++)
{
var source = _random.Next(p.Length);

var t = p[i];
p[i] = p[source];
p[source] = t;
}
}

/// <summary>
/// generate a new permutation.
/// </summary>
public static void Reseed()
{
CalculatePermutation(out _permutation);
}

private static void CalculateGradients(out Vector2[] grad)
{
grad = new Vector2[256];

for (var i = 0; i < grad.Length; i++)
{
Vector2 gradient;

do
{
gradient = new Vector2((float)(_random.NextDouble() * 2 - 1), (float)(_random.NextDouble() * 2 - 1));
}
while (gradient.LengthSquared() >= 1);

gradient.Normalize();

grad[i] = gradient;
}

}

private static float Drop(float t)
{
t = Math.Abs(t);
return 1f - t * t * t * (t * (t * 6 - 15) + 10);
}

private static float Q(float u, float v)
{
return Drop(u) * Drop(v);
}

public static float Noise(float x, float y)
{
var cell = new Vector2((float)Math.Floor(x), (float)Math.Floor(y));

var total = 0f;

var corners = new[] { new Vector2(0, 0), new Vector2(0, 1), new Vector2(1, 0), new Vector2(1, 1) };

foreach (var n in corners)
{
var ij = cell + n;
var uv = new Vector2(x - ij.X, y - ij.Y);

var index = _permutation[(int)ij.X % _permutation.Length];
index = _permutation[(index + (int)ij.Y) % _permutation.Length];

var grad = _gradients[index % _gradients.Length];

total += Q(uv.X, uv.Y) * Vector2.Dot(grad, uv);
}

return Math.Max(Math.Min(total, 1f), -1f);
}

}

这样调用它:

private void GenerateNoiseMap(int width, int height, ref Texture2D noiseTexture, int octaves)
{
var data = new float[width * height];

/// track min and max noise value. Used to normalize the result to the 0 to 1.0 range.
var min = float.MaxValue;
var max = float.MinValue;

/// rebuild the permutation table to get a different noise pattern.
/// Leave this out if you want to play with changing the number of octaves while
/// maintaining the same overall pattern.
Noise2d.Reseed();

var frequency = 0.5f;
var amplitude = 1f;
var persistence = 0.25f;

for (var octave = 0; octave < octaves; octave++)
{
/// parallel loop - easy and fast.
Parallel.For(0
, width * height
, (offset) =>
{
var i = offset % width;
var j = offset / width;
var noise = Noise2d.Noise(i*frequency*1f/width, j*frequency*1f/height);
noise = data[j * width + i] += noise * amplitude;

min = Math.Min(min, noise);
max = Math.Max(max, noise);

}
);

frequency *= 2;
amplitude /= 2;
}


if (noiseTexture != null && (noiseTexture.Width != width || noiseTexture.Height != height))
{
noiseTexture.Dispose();
noiseTexture = null;
}
if (noiseTexture==null)
{
noiseTexture = new Texture2D(Device, width, height, false, SurfaceFormat.Color);
}

var colors = data.Select(
(f) =>
{
var norm = (f - min) / (max - min);
return new Color(norm, norm, norm, 1);
}
).ToArray();

noiseTexture.SetData(colors);
}

请注意,我使用了几个 XNA 结构(Vector2 和 Texture2D),但它们的作用应该很清楚。

如果您想要更高频率(更“嘈杂”)且 Octave 音阶更少的内容,请增加 Octave 音阶循环中使用的初始频率值。

此实现使用“改进的”Perlin 噪声,它应该比标准版本快一点。您还可以查看 Simplex 噪声,它在更高维度上要快得多。

关于c# - 二维柏林噪声,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/8659351/

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