On Thu, 16 Feb 2006, james tittle wrote:
...as this last page shows, a simple gaussian blur is: #define KERNEL_SIZE 9 // Gaussian kernel // 1 2 1 // 2 4 2 // 1 2 1 const float kernel[KERNEL_SIZE] = { 1.0/16.0, 2.0/16.0,
At that level of detail (3 by 3) there isn't much to distinguish a gaussian blur from many other kinds of blur. Fortunately, the more you compose any blur with any blur, the closer you get to a gaussian blur. That's like, the biggest theorem in probability theory, which could as well be called "theory of blurred values".
i just mean that i wouldn't call the above "gaussian" but it can be close enough. Note that the above is the result of doing twice a 2x2 blur with the kernel 1 1 1 1.
_ _ __ ___ _____ ________ _____________ _____________________ ... | Mathieu Bouchard - tél:+1.514.383.3801 - http://artengine.ca/matju | Freelance Digital Arts Engineer, Montréal QC Canada