**Scale Space Implementation**

The **linear scale-space representation** of an N-dimensional continuous signal is obtained by convolving with an N-dimensional Gaussian kernel

However, for **implementation**, this definition is impractical, since it is continuous. When applying the scale space concept to a discrete signal, different approaches can be taken. This article is a brief summary of some of the most frequently used methods.

Read more about Scale Space Implementation: Separability, The Sampled Gaussian Kernel, The Discrete Gaussian Kernel, Recursive Filters, Finite-impulse-response (FIR) Smoothers, Real-time Implementation Within Pyramids and Discrete Approximation of Scale-normalized Derivatives, Other Multi-scale Approaches, See Also

### Other articles related to "scale space implementation":

**Scale Space Implementation**- See Also

... scale space pyramid (image processing) multi-scale approaches Gaussian filter. ...

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