title: Gaussian Blur - standard deviation, radius and kernel size
body: <p>I've implemented a gaussian blur fragment shader in GLSL. I understand the main concepts behind all of it: convolution, separation of x and y using linearity, multiple passes to increase radius...</p>
  
  <p>I still have a few questions though:</p>
  
  <p><strong>What's the relationship between sigma and radius?</strong></p>
  
  <p>I've read that sigma is equivalent to radius, I don't see how sigma is expressed in pixels. Or is "radius" just a name for sigma, not related to pixels?</p>
  
  <p><strong>How do I choose sigma?</strong></p>
  
  <p>Considering I use multiple passes to increase sigma, how do I choose a good sigma to obtain the sigma I want at any given pass? If the resulting sigma is equal to <em>the square root of the sum of the squares of the sigmas</em> and sigma is equivalent to radius, what's an easy way to get any desired radius?</p>
  
  <p><strong>What's the good size for a kernel, and how does it relate to sigma?</strong></p>
  
  <p>I've seen most implementations use a 5x5 kernel. This is probably a good choice for a fast implementation with decent quality, but is there another reason to choose another kernel size? How does sigma relate to the kernel size? Should I find the best sigma so that coefficients outside my kernel are negligible and just normalize?</p>