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A convolution in image space is a component-wise multiplication in fourier space. As the size of your convolution kernel increases, sometimes it is more effici

A convolution in image space is a component-wise multiplication in fourier space. As the size of your convolution kernel increases, sometimes it is more efficient to convert the kernel to fourier space, multiply pixel by pixel, and then convert back. This is what's going on with the presets at the bottom of the article.. for example, if you took the gaussian blur filter and converted it to image space, you'd have a gaussian blur convolution kernel.

smorrow 12y ago
> [...] convolution [...] component-wise multiplication in fourier space [...] convolution kernel [...] gaussian blur filter [...] Can I ask where people learn this stuff? Programming computers is pretty easy to learn by yourself, but the more I look at technical subjects other than programming computers, the less I can understand how it's possible to learn that stuff other than someone showing you.
- sharpneli 12y ago
  School. Books. Or the way I did it: Access to Matlab while in University. I learned signal processing just like I learned to program, by playing around and hacking stuff together. Naturally no-one learns anything in isolation. So bunch of reading is needed regardless of what you do.
- tfinniga 12y ago
  Learned this in my image/signal processing class at university. Most of the terms are just fancy / specific ways of saying simple things. There are a few key concepts to learn, and then the rest is implementation and learning the vocabulary so you can discuss it unambiguously.
- tripzilch 12y ago
  Many many years ago, a fellow demoscener pointed me to this: Yehar's DSP Tutorial for the Braindead http://yehar.com/blog/?p=121 http://yehar.com/blog/?p=121 It skips over some of the more fundamental math, but it serves as a great introduction to general ideas of digital signal processing. You can then proceed to look up the fiddly bits and deeper theory in more detail as you see fit (start from Wikipedia, hit the external links--that's how I'd do it). This particular tutorial speaks mainly about digital audio signal processing, which is the 1D case, but it generalizes to 2D image processing just as easily, if you've got the imagination (although you need some tricks if you don't want an IIR filter to look weird on an image).
tripzilch 12y ago
Interesting sidenote: The gaussian blur filter is pretty special in the sense that it has the same shape in both fourier-space (multiplication mask) as it does in pixel-space (convolution kernel).

smorrow 12y ago

> [...] convolution [...] component-wise multiplication in fourier space [...] convolution kernel [...] gaussian blur filter [...] Can I ask where people learn this stuff? Programming computers is pretty easy to learn by yourself, but the more I look at technical subjects other than programming computers, the less I can understand how it's possible to learn that stuff other than someone showing you.

sharpneli 12y ago
School. Books. Or the way I did it: Access to Matlab while in University. I learned signal processing just like I learned to program, by playing around and hacking stuff together. Naturally no-one learns anything in isolation. So bunch of reading is needed regardless of what you do.
tfinniga 12y ago
Learned this in my image/signal processing class at university. Most of the terms are just fancy / specific ways of saying simple things. There are a few key concepts to learn, and then the rest is implementation and learning the vocabulary so you can discuss it unambiguously.
tripzilch 12y ago
Many many years ago, a fellow demoscener pointed me to this: Yehar's DSP Tutorial for the Braindead http://yehar.com/blog/?p=121 http://yehar.com/blog/?p=121 It skips over some of the more fundamental math, but it serves as a great introduction to general ideas of digital signal processing. You can then proceed to look up the fiddly bits and deeper theory in more detail as you see fit (start from Wikipedia, hit the external links--that's how I'd do it). This particular tutorial speaks mainly about digital audio signal processing, which is the 1D case, but it generalizes to 2D image processing just as easily, if you've got the imagination (although you need some tricks if you don't want an IIR filter to look weird on an image).

tripzilch 12y ago

Interesting sidenote: The gaussian blur filter is pretty special in the sense that it has the same shape in both fourier-space (multiplication mask) as it does in pixel-space (convolution kernel).