Smoothing

This article is about a type of statistical technique for handling data. For other uses, see Smoothing (disambiguation).

In statistics and image processing, to smooth a data set is to create an approximating function that attempts to capture important patterns in the data, while leaving out noise or other fine-scale structures/rapid phenomena. In smoothing, the data points of a signal are modified so individual points higher than the adjacent points (presumably because of noise) are reduced, and points that are lower than the adjacent points are increased, leading to a smoother signal.

Reducing noise by smoothing may aid in data analysis in two notable ways:

  1. Help uncover more meaningful information from the underlying data, such as trends.
  2. Provide analyses that are both flexible and robust.

Many different algorithms are used in smoothing, most commonly binning, kernels, and local weighted regression.

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