Nearest-neighbor interpolation: Difference between revisions

Revision as of 16:41, 14 November 2024

Revision as of 16:48, 14 November 2024

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==Connection to Voronoi diagram==

For a given set of points in space, a [[Voronoi diagram]] is a decomposition of space into cells, one for each given point, so that anywhere in space, the closest given point is inside the cell. This is equivalent to nearest neighbor interpolation, by assigning the function value at the given point to all the points inside the cell.<ref>{{cite web |last1=Hartmann |first1=K. |last2=Krois |first2=J. |last3=Rudolph |first3=A. |year=2023 |title=Statistics and Geodata Analysis using R (SOGA-R) |publisher=Department of Earth Sciences, Freie Universität Berlin |url=https://www.geo.fu-berlin.de/en/ |accessdate=2024-11-14}}</ref> The figures on the right side show by color the shape of the cells.

{{comparison_of_1D_and_2D_interpolation.svg|left}}

[[Image:Coloured_Voronoi_2D.svg|none|thumb|This [[Voronoi diagram]] is an example of nearest neighbor interpolation of a random set of points (black dots) in 2D.]]

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==See also==