简单的噪音产生


27

我正在寻找产生如下噪声:

在此处输入图片说明在此处输入图片说明

(图片由了解Perlin噪声提供

我基本上是在寻找带有许多小“波纹”的噪音。以下是不可取的:

在此处输入图片说明

有没有简单的方法可以做到这一点?我已经看了一个星期的perlin和simplex,似乎无法在JavaScript中使用它,或者当我这样做时,我没有正确的参数来生成此类图像,或者这太令人费解了慢。

我了解我发布的3张图像可能可以通过相同的算法来实现,但比例不同,但是我不需要那种算法。我只需要一个非常简单的算法即可理想地实现类似第一张图片中的效果。也许某种模糊可以胜任,但我无法取得结果。

我正在用JavaScript开发此工具,但是任何类型的代码,甚至是简单而详细的说明都可以使用。


3
仅供参考,您想要的显然是Perlin噪音。您提到的“不良”效果是由几个倍频的Perlin噪声(彼此称为分形噪声)组成的。您是否真的只需要一张图像,还是希望它随时间变化?如果是这样,您会产生什么影响?
sam hocevar 2011年

@SamHocevar我想即时生成它。我希望重现此问题中提到的内容。
Xeon06

我找到了这种JS perlin噪声实现,并将其集成到jsFiddle中。但是,结果与Flash中的Perlin噪声实现完全不同,这使我想知道Flash附带的Perlin噪声生成器的实现细节。
bummzack 2011年

@bummzack确实,看来Flash生成器出于我的目的会产生完美的噪声。我无法与您发布的小提琴打交道。
Xeon06

我也对此感兴趣,因此我对stackoverflow提出了一个问题。希望我们在那里能得到一些答案。
bummzack 2011年

Answers:


16

虽然现有答案提供了一种很好的方法来实现问题中所显示的图像,但注释显示,目标是生成如下所示的图像:

佩林噪声湍流

这种噪声与问题图像中所示的噪声完全不同,因为它形成了封闭的孤立斑点。

事实证明,这种噪声称为湍流(根据此CPU Gems文章),其实现方式如下(其中noise,Perlin-noise函数返回的值从-1..1开始):

double turbulence(double x, double y, double z, double f) {
    double t = -.5;
    for ( ; f <= W/12 ; f *= 2) // W = Image width in pixels
        t += abs(noise(x,y,z,f) / f);
    return t;
}

用上述湍流功能混搭此JavaScript Perlin-noise实现会产生噪声,该噪声与上图非常相似:

湍流噪声

可以在此jsFiddle中找到用于生成上述图像的JavaScript代码。


3
那是一些奇怪的代码,JavaScript版本与Java版本完全不同,并且JavaScript版本基本上是一种完全错误的编写方式return Math.abs(this.noise(x,y,z)*2)-.5
aaaaaaaaaaaaaa

@aaaaaaaaaaaaaa与Ken Perlin亲自学习,他编写了该特定代码块。
b1nary.atr0phy

15

您的示例图像看起来很像粉红色噪点。它是这样生成的:

  • 首先,我们有某种平滑的随机噪声。通常,这是通过在具有整数坐标的点上计算伪随机值并以某种方式内插这些值来实现的。此阶段的结果如下所示:

    在此处输入图片说明

  • 接下来,我们处理此噪声并对其进行“压缩”,以增加其频率。最简单的公式是n2(x,y)= n1(x f,y f)。这样,两个方向上的噪声模式都被压缩了f倍。更好的噪声算法还在此步骤旋转和/或转换噪声模式,以打破规律性。

  • 然后,将此压缩的模式乘以某个值(小于1),然后添加到第一个模式。实际上,我们在低频模式的顶部添加了较小的高频变化。结果看起来像这样:

    在此处输入图片说明

  • 步骤2和3可以重复多次,从而增加了越来越精细的细节。最终结果通常看起来像您带有红叉的示例。但是,请注意,我们的算法中有3个参数可以使用:

    • 八度计数-换句话说,生成的步数。步骤越多,表示所得图案中的细节越细。
    • 坚持不懈。这个价值在每一步中都成倍增加。通常,持久性在0到1之间。高持久性值通常会产生“噪点”模式,但细节很少。低持久性可创建具有精细细节的平滑模式。
    • 腔隙。这是我们每步使用的“压缩”系数。狭cu的工作有点像持久性,但不完全相同。低盲点产生更平滑的图案,高盲点产生更清晰和高对比度的图案。

这里有些例子:

高持久性: 高持久性噪声

高腔隙性: 高腔隙噪声

低腔隙: 低腔隙噪音

玩这些参数并不是您唯一能做的。可以在噪声模式中添加字符的一种不错的技术是使用扰动,即在噪声函数的输入坐标中添加一些噪声。

例如,假设您有一些函数会在给定坐标和随机种子的情况下生成噪声:Noise(x,y, seed)。比您可以使用类似的方法Noise(x+Noise(x,y,234), y+Noise(x,y,6544), seed)来获得扰动的价值。这可能会导致这样的模式(摄动在此处应用于圆形模式,而不是噪声):

湍流

如果您想了解更多信息,建议您看一下libnoise(C ++)或CoherentNoise(C#)。不幸的是,我不知道任何Javascript噪声生成库。


6

代码已注释。归功于Sean McCullough。 http://staffwww.itn.liu.se/~stegu/simplexnoise/simplexnoise.pdf

// Ported from Stefan Gustavson's java implementation
// http://staffwww.itn.liu.se/~stegu/simplexnoise/simplexnoise.pdf
// Read Stefan's excellent paper for details on how this code works.
//
// Sean McCullough banksean@gmail.com

/**
* You can pass in a random number generator object if you like.
* It is assumed to have a random() method.
*/
var SimplexNoise = function(r) {
if (r == undefined) r = Math;
  this.grad3 = [[1,1,0],[-1,1,0],[1,-1,0],[-1,-1,0],
                                 [1,0,1],[-1,0,1],[1,0,-1],[-1,0,-1],
                                 [0,1,1],[0,-1,1],[0,1,-1],[0,-1,-1]];
  this.p = [];
  for (var i=0; i<256; i++) {
this.p[i] = Math.floor(r.random()*256);
  }
  // To remove the need for index wrapping, double the permutation table length
  this.perm = [];
  for(var i=0; i<512; i++) {
this.perm[i]=this.p[i & 255];
}

  // A lookup table to traverse the simplex around a given point in 4D.
  // Details can be found where this table is used, in the 4D noise method.
  this.simplex = [
    [0,1,2,3],[0,1,3,2],[0,0,0,0],[0,2,3,1],[0,0,0,0],[0,0,0,0],[0,0,0,0],[1,2,3,0],
    [0,2,1,3],[0,0,0,0],[0,3,1,2],[0,3,2,1],[0,0,0,0],[0,0,0,0],[0,0,0,0],[1,3,2,0],
    [0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],
    [1,2,0,3],[0,0,0,0],[1,3,0,2],[0,0,0,0],[0,0,0,0],[0,0,0,0],[2,3,0,1],[2,3,1,0],
    [1,0,2,3],[1,0,3,2],[0,0,0,0],[0,0,0,0],[0,0,0,0],[2,0,3,1],[0,0,0,0],[2,1,3,0],
    [0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],
    [2,0,1,3],[0,0,0,0],[0,0,0,0],[0,0,0,0],[3,0,1,2],[3,0,2,1],[0,0,0,0],[3,1,2,0],
    [2,1,0,3],[0,0,0,0],[0,0,0,0],[0,0,0,0],[3,1,0,2],[0,0,0,0],[3,2,0,1],[3,2,1,0]];
};

SimplexNoise.prototype.dot = function(g, x, y) {
return g[0]*x + g[1]*y;
};

SimplexNoise.prototype.noise = function(xin, yin) {
  var n0, n1, n2; // Noise contributions from the three corners
  // Skew the input space to determine which simplex cell we're in
  var F2 = 0.5*(Math.sqrt(3.0)-1.0);
  var s = (xin+yin)*F2; // Hairy factor for 2D
  var i = Math.floor(xin+s);
  var j = Math.floor(yin+s);
  var G2 = (3.0-Math.sqrt(3.0))/6.0;
  var t = (i+j)*G2;
  var X0 = i-t; // Unskew the cell origin back to (x,y) space
  var Y0 = j-t;
  var x0 = xin-X0; // The x,y distances from the cell origin
  var y0 = yin-Y0;
  // For the 2D case, the simplex shape is an equilateral triangle.
  // Determine which simplex we are in.
  var i1, j1; // Offsets for second (middle) corner of simplex in (i,j) coords
  if(x0>y0) {i1=1; j1=0;} // lower triangle, XY order: (0,0)->(1,0)->(1,1)
  else {i1=0; j1=1;} // upper triangle, YX order: (0,0)->(0,1)->(1,1)
  // A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and
  // a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where
  // c = (3-sqrt(3))/6
  var x1 = x0 - i1 + G2; // Offsets for middle corner in (x,y) unskewed coords
  var y1 = y0 - j1 + G2;
  var x2 = x0 - 1.0 + 2.0 * G2; // Offsets for last corner in (x,y) unskewed coords
  var y2 = y0 - 1.0 + 2.0 * G2;
  // Work out the hashed gradient indices of the three simplex corners
  var ii = i & 255;
  var jj = j & 255;
  var gi0 = this.perm[ii+this.perm[jj]] % 12;
  var gi1 = this.perm[ii+i1+this.perm[jj+j1]] % 12;
  var gi2 = this.perm[ii+1+this.perm[jj+1]] % 12;
  // Calculate the contribution from the three corners
  var t0 = 0.5 - x0*x0-y0*y0;
  if(t0<0) n0 = 0.0;
  else {
    t0 *= t0;
    n0 = t0 * t0 * this.dot(this.grad3[gi0], x0, y0); // (x,y) of grad3 used for 2D gradient
  }
  var t1 = 0.5 - x1*x1-y1*y1;
  if(t1<0) n1 = 0.0;
  else {
    t1 *= t1;
    n1 = t1 * t1 * this.dot(this.grad3[gi1], x1, y1);
  }
  var t2 = 0.5 - x2*x2-y2*y2;
  if(t2<0) n2 = 0.0;
  else {
    t2 *= t2;
    n2 = t2 * t2 * this.dot(this.grad3[gi2], x2, y2);
  }
  // Add contributions from each corner to get the final noise value.
  // The result is scaled to return values in the interval [-1,1].
  return 70.0 * (n0 + n1 + n2);
};

// 3D simplex noise
SimplexNoise.prototype.noise3d = function(xin, yin, zin) {
  var n0, n1, n2, n3; // Noise contributions from the four corners
  // Skew the input space to determine which simplex cell we're in
  var F3 = 1.0/3.0;
  var s = (xin+yin+zin)*F3; // Very nice and simple skew factor for 3D
  var i = Math.floor(xin+s);
  var j = Math.floor(yin+s);
  var k = Math.floor(zin+s);
  var G3 = 1.0/6.0; // Very nice and simple unskew factor, too
  var t = (i+j+k)*G3;
  var X0 = i-t; // Unskew the cell origin back to (x,y,z) space
  var Y0 = j-t;
  var Z0 = k-t;
  var x0 = xin-X0; // The x,y,z distances from the cell origin
  var y0 = yin-Y0;
  var z0 = zin-Z0;
  // For the 3D case, the simplex shape is a slightly irregular tetrahedron.
  // Determine which simplex we are in.
  var i1, j1, k1; // Offsets for second corner of simplex in (i,j,k) coords
  var i2, j2, k2; // Offsets for third corner of simplex in (i,j,k) coords
  if(x0>=y0) {
    if(y0>=z0)
      { i1=1; j1=0; k1=0; i2=1; j2=1; k2=0; } // X Y Z order
      else if(x0>=z0) { i1=1; j1=0; k1=0; i2=1; j2=0; k2=1; } // X Z Y order
      else { i1=0; j1=0; k1=1; i2=1; j2=0; k2=1; } // Z X Y order
    }
  else { // x0<y0
    if(y0<z0) { i1=0; j1=0; k1=1; i2=0; j2=1; k2=1; } // Z Y X order
    else if(x0<z0) { i1=0; j1=1; k1=0; i2=0; j2=1; k2=1; } // Y Z X order
    else { i1=0; j1=1; k1=0; i2=1; j2=1; k2=0; } // Y X Z order
  }
  // A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z),
  // a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and
  // a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where
  // c = 1/6.
  var x1 = x0 - i1 + G3; // Offsets for second corner in (x,y,z) coords
  var y1 = y0 - j1 + G3;
  var z1 = z0 - k1 + G3;
  var x2 = x0 - i2 + 2.0*G3; // Offsets for third corner in (x,y,z) coords
  var y2 = y0 - j2 + 2.0*G3;
  var z2 = z0 - k2 + 2.0*G3;
  var x3 = x0 - 1.0 + 3.0*G3; // Offsets for last corner in (x,y,z) coords
  var y3 = y0 - 1.0 + 3.0*G3;
  var z3 = z0 - 1.0 + 3.0*G3;
  // Work out the hashed gradient indices of the four simplex corners
  var ii = i & 255;
  var jj = j & 255;
  var kk = k & 255;
  var gi0 = this.perm[ii+this.perm[jj+this.perm[kk]]] % 12;
  var gi1 = this.perm[ii+i1+this.perm[jj+j1+this.perm[kk+k1]]] % 12;
  var gi2 = this.perm[ii+i2+this.perm[jj+j2+this.perm[kk+k2]]] % 12;
  var gi3 = this.perm[ii+1+this.perm[jj+1+this.perm[kk+1]]] % 12;
  // Calculate the contribution from the four corners
  var t0 = 0.6 - x0*x0 - y0*y0 - z0*z0;
  if(t0<0) n0 = 0.0;
  else {
    t0 *= t0;
    n0 = t0 * t0 * this.dot(this.grad3[gi0], x0, y0, z0);
  }
  var t1 = 0.6 - x1*x1 - y1*y1 - z1*z1;
  if(t1<0) n1 = 0.0;
  else {
    t1 *= t1;
    n1 = t1 * t1 * this.dot(this.grad3[gi1], x1, y1, z1);
  }
  var t2 = 0.6 - x2*x2 - y2*y2 - z2*z2;
  if(t2<0) n2 = 0.0;
  else {
    t2 *= t2;
    n2 = t2 * t2 * this.dot(this.grad3[gi2], x2, y2, z2);
  }
  var t3 = 0.6 - x3*x3 - y3*y3 - z3*z3;
  if(t3<0) n3 = 0.0;
  else {
    t3 *= t3;
    n3 = t3 * t3 * this.dot(this.grad3[gi3], x3, y3, z3);
  }
  // Add contributions from each corner to get the final noise value.
  // The result is scaled to stay just inside [-1,1]
  return 32.0*(n0 + n1 + n2 + n3);
};

另外,如果您使用PRNG,则可以轻松获得容易恢复的结果

/*
  I've wrapped Makoto Matsumoto and Takuji Nishimura's code in a namespace
  so it's better encapsulated. Now you can have multiple random number generators
  and they won't stomp all over eachother's state.

  If you want to use this as a substitute for Math.random(), use the random()
  method like so:

  var m = new MersenneTwister();
  var randomNumber = m.random();

  You can also call the other genrand_{foo}() methods on the instance.

  If you want to use a specific seed in order to get a repeatable random
  sequence, pass an integer into the constructor:

  var m = new MersenneTwister(123);

  and that will always produce the same random sequence.

  Sean McCullough (banksean@gmail.com)
*/

/* 
   A C-program for MT19937, with initialization improved 2002/1/26.
   Coded by Takuji Nishimura and Makoto Matsumoto.

   Before using, initialize the state by using init_genrand(seed)  
   or init_by_array(init_key, key_length).

   Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
   All rights reserved.                          

   Redistribution and use in source and binary forms, with or without
   modification, are permitted provided that the following conditions
   are met:

     1. Redistributions of source code must retain the above copyright
        notice, this list of conditions and the following disclaimer.

     2. Redistributions in binary form must reproduce the above copyright
        notice, this list of conditions and the following disclaimer in the
        documentation and/or other materials provided with the distribution.

     3. The names of its contributors may not be used to endorse or promote 
        products derived from this software without specific prior written 
        permission.

   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
   "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
   LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
   A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
   CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
   EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
   PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
   PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
   LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
   NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
   SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.


   Any feedback is very welcome.
   http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
   email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
*/

var MersenneTwister = function(seed) {
  if (seed == undefined) {
    seed = new Date().getTime();
  } 
  /* Period parameters */  
  this.N = 624;
  this.M = 397;
  this.MATRIX_A = 0x9908b0df;   /* constant vector a */
  this.UPPER_MASK = 0x80000000; /* most significant w-r bits */
  this.LOWER_MASK = 0x7fffffff; /* least significant r bits */

  this.mt = new Array(this.N); /* the array for the state vector */
  this.mti=this.N+1; /* mti==N+1 means mt[N] is not initialized */

  this.init_genrand(seed);
}  

/* initializes mt[N] with a seed */
MersenneTwister.prototype.init_genrand = function(s) {
  this.mt[0] = s >>> 0;
  for (this.mti=1; this.mti<this.N; this.mti++) {
      var s = this.mt[this.mti-1] ^ (this.mt[this.mti-1] >>> 30);
   this.mt[this.mti] = (((((s & 0xffff0000) >>> 16) * 1812433253) << 16) + (s & 0x0000ffff) * 1812433253)
  + this.mti;
      /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
      /* In the previous versions, MSBs of the seed affect   */
      /* only MSBs of the array mt[].                        */
      /* 2002/01/09 modified by Makoto Matsumoto             */
      this.mt[this.mti] >>>= 0;
      /* for >32 bit machines */
  }
}

/* initialize by an array with array-length */
/* init_key is the array for initializing keys */
/* key_length is its length */
/* slight change for C++, 2004/2/26 */
MersenneTwister.prototype.init_by_array = function(init_key, key_length) {
  var i, j, k;
  this.init_genrand(19650218);
  i=1; j=0;
  k = (this.N>key_length ? this.N : key_length);
  for (; k; k--) {
    var s = this.mt[i-1] ^ (this.mt[i-1] >>> 30)
    this.mt[i] = (this.mt[i] ^ (((((s & 0xffff0000) >>> 16) * 1664525) << 16) + ((s & 0x0000ffff) * 1664525)))
      + init_key[j] + j; /* non linear */
    this.mt[i] >>>= 0; /* for WORDSIZE > 32 machines */
    i++; j++;
    if (i>=this.N) { this.mt[0] = this.mt[this.N-1]; i=1; }
    if (j>=key_length) j=0;
  }
  for (k=this.N-1; k; k--) {
    var s = this.mt[i-1] ^ (this.mt[i-1] >>> 30);
    this.mt[i] = (this.mt[i] ^ (((((s & 0xffff0000) >>> 16) * 1566083941) << 16) + (s & 0x0000ffff) * 1566083941))
      - i; /* non linear */
    this.mt[i] >>>= 0; /* for WORDSIZE > 32 machines */
    i++;
    if (i>=this.N) { this.mt[0] = this.mt[this.N-1]; i=1; }
  }

  this.mt[0] = 0x80000000; /* MSB is 1; assuring non-zero initial array */ 
}

/* generates a random number on [0,0xffffffff]-interval */
MersenneTwister.prototype.genrand_int32 = function() {
  var y;
  var mag01 = new Array(0x0, this.MATRIX_A);
  /* mag01[x] = x * MATRIX_A  for x=0,1 */

  if (this.mti >= this.N) { /* generate N words at one time */
    var kk;

    if (this.mti == this.N+1)   /* if init_genrand() has not been called, */
      this.init_genrand(5489); /* a default initial seed is used */

    for (kk=0;kk<this.N-this.M;kk++) {
      y = (this.mt[kk]&this.UPPER_MASK)|(this.mt[kk+1]&this.LOWER_MASK);
      this.mt[kk] = this.mt[kk+this.M] ^ (y >>> 1) ^ mag01[y & 0x1];
    }
    for (;kk<this.N-1;kk++) {
      y = (this.mt[kk]&this.UPPER_MASK)|(this.mt[kk+1]&this.LOWER_MASK);
      this.mt[kk] = this.mt[kk+(this.M-this.N)] ^ (y >>> 1) ^ mag01[y & 0x1];
    }
    y = (this.mt[this.N-1]&this.UPPER_MASK)|(this.mt[0]&this.LOWER_MASK);
    this.mt[this.N-1] = this.mt[this.M-1] ^ (y >>> 1) ^ mag01[y & 0x1];

    this.mti = 0;
  }

  y = this.mt[this.mti++];

  /* Tempering */
  y ^= (y >>> 11);
  y ^= (y << 7) & 0x9d2c5680;
  y ^= (y << 15) & 0xefc60000;
  y ^= (y >>> 18);

  return y >>> 0;
}

/* generates a random number on [0,0x7fffffff]-interval */
MersenneTwister.prototype.genrand_int31 = function() {
  return (this.genrand_int32()>>>1);
}

/* generates a random number on [0,1]-real-interval */
MersenneTwister.prototype.genrand_real1 = function() {
  return this.genrand_int32()*(1.0/4294967295.0); 
  /* divided by 2^32-1 */ 
}

/* generates a random number on [0,1)-real-interval */
MersenneTwister.prototype.random = function() {
  return this.genrand_int32()*(1.0/4294967296.0); 
  /* divided by 2^32 */
}

/* generates a random number on (0,1)-real-interval */
MersenneTwister.prototype.genrand_real3 = function() {
  return (this.genrand_int32() + 0.5)*(1.0/4294967296.0); 
  /* divided by 2^32 */
}

/* generates a random number on [0,1) with 53-bit resolution*/
MersenneTwister.prototype.genrand_res53 = function() { 
  var a=this.genrand_int32()>>>5, b=this.genrand_int32()>>>6; 
  return(a*67108864.0+b)*(1.0/9007199254740992.0); 
} 

/* These real versions are due to Isaku Wada, 2002/01/09 added */

0

使用预先生成的纹理,或将perlin噪声纹理生成器放置在服务器上,并向其查询perlin噪声图像。


我已经在服务器上执行此操作,并且需要生成纹理。
Xeon06

如果您在服务器上执行此操作,为什么需要javascript?您还可以使用哪些其他技术?
sam hocevar 2011年

@SamHocevar我正在服务器上使用JavaScript进行操作。Node.js。
Xeon06

@ Xenon06:如果您追求性能,我真的认为您将需要本机代码;幸运的是,您可以使用C ++编写Node.js扩展
sam hocevar,2011年

@SamHocevar很酷,谢谢您的链接,我会检查我的性能是否不好
Xeon06 2011年
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