Convolution Image convolution is one the easiest techniques to learn in computer vision and it's a technique that illustrates the power of local feature detection better than weeks of lecture. In principle, convolution involves nothing more than repeatedly applying an NxN matrix to a pixel and its neighbors. Depending on the matrix scalars several different effects can be achieved: Blur Edge Detection <--- Let's focus on this Sharpen Edge detection is one of the fundamental…

# Gaussian Blur

Here is an old script to apply a gaussian blur to an image using a 5x5 convolution matrix (see Kernel as well) based on the following formula: [math]G(x,y)=\frac{1}{2\pi\sigma^{2}}\epsilon^{-(x^{2}+y^{2})/2\sigma^{2}}[/math] Original script used CImg version 1-13 (something like 30 revisions ago :) ) I think my snippet is easy enough to follow that the image library I used shouldn't really matter.…