Natural-neighbor interpolation or Sibson interpolation is a method of spatial interpolation, developed by Robin Sibson. The method is based on Voronoi...

Nearest-neighbor interpolation (also known as proximal interpolation or, in some contexts, point sampling) is a simple method of multivariate interpolation in...

corresponding surfaces obtained by bilinear interpolation or nearest-neighbor interpolation. Bicubic interpolation can be accomplished using either Lagrange...

tricubic interpolation) Kriging Inverse distance weighting Natural neighbor interpolation Spline interpolation Radial basis function interpolation Barnes...

partitioning the space is used to create each of these elements. Natural neighbor interpolation functions are then used to model the unknown function within...

Delaunay triangulation Map segmentation Natural element method Natural neighbor interpolation Nearest-neighbor interpolation Power diagram Voronoi pole Burrough...

which are undesirable for surface analysis. Additionally, natural neighbor interpolation and Thiessen (Voronoi) polygon generation can only be performed...

include nearest-neighbor interpolation, bilinear interpolation and bicubic interpolation in two dimensions, and trilinear interpolation in three dimensions...

linear interpolation and bilinear interpolation Lanczos resampling — based on convolution with a sinc function Natural neighbor interpolation PDE surface...

nearest neighbors. If k = 1, then the output is simply assigned to the value of that single nearest neighbor, also known as nearest neighbor interpolation. For...

instances of the same color component. The simplest method is nearest-neighbor interpolation which simply copies an adjacent pixel of the same color channel...

data Nearest-neighbor interpolation Tricubic interpolation: a generalization of cubic interpolation to three dimensions Pareto interpolation: a method of...

polyharmonic splines are used for function approximation and data interpolation. They are very useful for interpolating and fitting scattered data in...

likely to be located near the end of the array. A common interpolation function is linear interpolation. If A {\displaystyle A} is the array, L , R {\displaystyle...

cell index, to describe the output geometry for the cell. Apply linear interpolation along the boundaries of the cell to calculate the exact contour position...

(/ˈkriːɡɪŋ/), also known as Gaussian process regression, is a method of interpolation based on Gaussian process governed by prior covariances. Under suitable...

BCE), the counsellor of Chandragupta Maurya, is implied in a later interpolation, reinforced by Gupta-era and medieval traditions, which explicitly identified...

this fashion, but instead through independent considerations. Linear interpolation (e.g., taking the weighted mean of the unigram, bigram, and trigram)...

contouring such as kriging, rather than relying on visual interpolation. The Natural Neighbour interpolation method allows isoseismals to be drawn in an objective...

that partially pass behind the camera. Nearest-neighbor interpolation Simplest form of interpolation that for given position outputs the color of the...

geostatistics, Kriging or Gaussian process regression is a method of interpolation for which the interpolated values are modeled by a Gaussian process...

a mesh, but are rather based on interaction of each node with all its neighbors. As a consequence, original extensive properties such as mass or kinetic...

poorly localized along an edge. First, for each candidate keypoint, interpolation of nearby data is used to accurately determine its position. The initial...

of simpler interpolation methods/algorithms, such as inverse distance weighting, bilinear interpolation and nearest-neighbor interpolation, were already...

Most of the physical properties of astatine have been estimated (by interpolation or extrapolation), using theoretically or empirically derived methods...

various architectural improvements. For example, they proposed log-space interpolation during backward sampling. Instead of sampling from x t − 1 ∼ N ( μ ~...

known location during some of the conception periods – but editorial interpolation of footnotes by Jordan with additional records closed those gaps in...

Gaussian processes are thus useful as a powerful non-linear multivariate interpolation tool. Kriging is also used to extend Gaussian process in the case of...

polynomial interpolation. In particular, it can be used to compute the divided difference coefficients of the Newton form of the interpolation polynomial...

axis by 180 degrees. Scaling is necessary because the plot is based on interpolation (linear combination) of consecutive pairs of variables. Therefore, the...