Engineering Image Processing: Convolution vs Filtering

[Master1022]

Homework Statement

What is the intuitive difference in terms of use case for the convolution operation as opposed to filtering?

Relevant Equations

Convolution and filtering of images

Hi,

So my question is perhaps better asked as:
- What is the point of convolution (in 2D image processing)?
- Why would we use that operation in image processing?
- What is so special about that flipped version of the kernel?

Context:
In an image processing class, I was learning about the operations of convolution and filtering. This post here basically summarises my current knowledge of the differences between the two operations.
- Filtering: we pass a mask over an image and calculate a 'dot-product' type calculation at each point and place that value in the corresponding pixel of the output image

- Convolution: First we flip the mask both top to bottom and left to right and then pass that over the image. As above, we calculate a 'dot-product' type calculation and put that into the corresponding pixel of the output.

I struggle to see why this operation is useful in practice.

Any advice is greatly appreciated. Also, please do let me know if another forum was more suitable for this post - I was unsure of where to put this information engineering question.

 

[.Scott]

Given your description of filtering and convolution, they are equivalent.
But there is another method for doing the same thing: Perform an FFT on the image and the filter; Multiply the two FFTs together to generate a new FFT; Perform an inverse FFT on the result.