卷积矩阵算法

Question

有人可以帮我理解卷积矩阵如何对图像产生影响吗？我知道像素的值（每个通道，红色，绿色和蓝色）是作为原始数据矩阵的总和而获得的使用卷积矩阵，但我没有得到算法。我有一个从网站上取得的一个例子，它会对图像产生模糊效果。你能帮我解释一下这些步骤吗？

Filters.tmpCanvas = document.createElement('canvas');
Filters.tmpCtx = Filters.tmpCanvas.getContext('2d');

Filters.createImageData = function(w,h) {
  return this.tmpCtx.createImageData(w,h);
};

Filters.convolute = function(pixels, weights, opaque) {
  var side = Math.round(Math.sqrt(weights.length));
  var halfSide = Math.floor(side/2);
  var src = pixels.data;
  var sw = pixels.width;
  var sh = pixels.height;
  // pad output by the convolution matrix
  var w = sw;
  var h = sh;
  var output = Filters.createImageData(w, h);
  var dst = output.data;
  // go through the destination image pixels
  var alphaFac = opaque ? 1 : 0;
  for (var y=0; y<h; y++) {
    for (var x=0; x<w; x++) {
      var sy = y;
      var sx = x;
      var dstOff = (y*w+x)*4;
      // calculate the weighed sum of the source image pixels that
      // fall under the convolution matrix
      var r=0, g=0, b=0, a=0;
      for (var cy=0; cy<side; cy++) {
        for (var cx=0; cx<side; cx++) {
          var scy = sy + cy - halfSide;
          var scx = sx + cx - halfSide;
          if (scy >= 0 && scy < sh && scx >= 0 && scx < sw) {
            var srcOff = (scy*sw+scx)*4;
            var wt = weights[cy*side+cx];
            r += src[srcOff] * wt;
            g += src[srcOff+1] * wt;
            b += src[srcOff+2] * wt;
            a += src[srcOff+3] * wt;
          }
        }
      }
      dst[dstOff] = r;
      dst[dstOff+1] = g;
      dst[dstOff+2] = b;
      dst[dstOff+3] = a + alphaFac*(255-a);
    }
  }
  return output;
};