# Why correlation is not associative in the context of image processing?

I can see most of the places it says "convolution is associative, while correlation, in general, is not".

Denote $*$ convolution operator, let's say you have an image $f$, which you need to convolve with $g$ and then with $h$ : $$f∗g∗h=f∗(g∗h)$$

But when I see the difference between convolution and correlation, correlation is equal to convolution but after flipping the kernel or window.

Can somebody explain with an example why correlation is not associative?

• @OlliNiemitalo, done. It's below my usual standard for an answer, but I'm working on becoming less pedantic anyway ... ;) – Jazzmaniac Oct 18 '17 at 22:01