如何为您的空间定义一个任意分辨率，并为该矩阵中的每个点计算从该点到所有点的距离的度量，然后可以制作一个“热图”并使用阈值来定义聚类。

这是一个很好的处理过程，也许以后我会发布解决方案。

编辑：

这里是：

//load the image
PImage sample;
sample = loadImage("test.png");
size(sample.width, sample.height);
image(sample, 0, 0);
int[][] heat = new int[width][height];

//parameters
int resolution = 5; //distance between points in the gridq
int distance = 8; //distance at wich two points are considered near
float threshold = 0.5;
int level = 240; //leven to detect the dots
int sensitivity = 1; //how much does each dot matters

//calculate the "heat" on each point of the grid
color black = color(0,0,0);
loadPixels();
for(int a=0; a<width; a+=resolution){
  for(int b=0; b<height; b+=resolution){
    for(int x=0; x<width; x++){
      for(int y=0; y<height; y++){
        color c = sample.pixels[y*sample.width+x];        
        /**
         * the heat should be a function of the brightness and the distance, 
         * but this works (tm)
         */
        if(brightness(c)<level && dist(x,y,a,b)<distance){
          heat[a][b] += sensitivity;
        }
      }
    }
  }
}

//render the output
for(int a=0; a<width; ++a){
  for(int b=0; b<height; ++b){
    pixels[b*sample.width+a] = color(heat[a][b],0,0);
  }
}
updatePixels();
filter(THRESHOLD,threshold);

编辑2（低效率代码少但输出相同）：

//load the image
PImage sample;
sample = loadImage("test.png");
size(sample.width, sample.height);
image(sample, 0, 0);
int[][] heat = new int[width][height];
int dotQ = 0;
int[][] dots = new int[width*height][2];
int X = 0;
int Y = 1;


//parameters
int resolution = 1; //distance between points in the grid
int distance = 20; //distance at wich two points are considered near
float threshold = 0.6;
int level = 240; //minimum brightness to detect the dots
int sensitivity = 1; //how much does each dot matters

//detect all dots in the sample
loadPixels();
for(int x=0; x<width; x++){
 for(int y=0; y<height; y++){
   color c = pixels[y*sample.width+x];
   if(brightness(c)<level) {
       dots[dotQ][X] += x;
       dots[dotQ++][Y] += y;
   }
 }
}

//calculate heat
for(int x=0; x<width; x+=resolution){
 for(int y=0; y<height; y+=resolution){
   for(int d=0; d<dotQ; d++){
     if(dist(x,y,dots[d][X],dots[d][Y]) < distance)
       heat[x][y]+=sensitivity;
   }
 }
}

//render the output
for(int a=0; a<width; ++a){
 for(int b=0; b<height; ++b){
   pixels[b*sample.width+a] = color(heat[a][b],0,0);
 }
}
updatePixels();
filter(THRESHOLD,threshold);

/** This smooths the ouput with low resolutions
* for(int i=0; i<10; ++i) filter(DILATE);
* for(int i=0; i<3; ++i) filter(BLUR);
* filter(THRESHOLD);
*/

和带有（减少的）Kent样本的输出：