Smoothing
From Wikipedia, the free encyclopedia
In statistics and image processing, to smooth a data set is to create a function that attempts to capture important patterns in the data, while leaving out noise. Many different algorithms are used in smoothing. One of the most common algorithms is the "moving average", often used to try to capture important trends in repeated statistical surveys. In image processing and computer vision, the most well-founded approach is scale-space representation.
[edit] See also
- Butterworth filter
- Recursive filter
- Kalman filter
- Scale space
- Cat Smoothing
[edit] External links
- Chapter on data smoothing from the instruction manual for Wolfram Research's Mathematica
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