Use of interp2 in an arbitrary dataset (2024)

FAQs

How does interp2 work? ›

The interp2 command interpolates between data points. It finds values of a two-dimensional function underlying the data at intermediate points. Interpolation is the same operation as table lookup.

Two dimensional interpolation takes a series of (x,y,z) points and generates estimated values for z's at new (x,y) points. Interpolation is used when the function that generated the original (x,y,z) points is unknown. Interpolation is related to, but distinct from, fitting a function to a series of points.

The basic idea of interpolation is quite simple: first, reconstruct a “continuous” image from the discrete input image, then sample this “continuous” image onto the grid of the output image. Interpolation methods differ from the way the “continuous” image is reconstructed.

Among its disadvantages is that its solution it is not very precise and data points is not differentiable. Bicubic interpolation in two dimensions, and trilinear interpolation in three dimensions are used when working on gridded or scattered data.

Linear interpolation of scattered data requires a mesh to be constructed using known independent points. This can be done using Delaunay triangulation to obtain simplexes (triangles or their higher dimensional equivalents) for the interpolation function to be applied over.

In terms of the ability to fit your data and produce a smooth surface, the Multiquadric method is considered by many to be the best. All of the Radial Basis Function methods are exact interpolators, so they attempt to honor your data.

Motion interpolation is a process done by high refresh displays where generated frames are inserted between the original frames of a video. Motion interpolation was added to modern LCD televisions to reduce motion blur and make the picture appear smoother and sharper.

In computer programming, string interpolation (or variable interpolation, variable substitution, or variable expansion) is the process of evaluating a string literal containing one or more placeholders, yielding a result in which the placeholders are replaced with their corresponding values.

That is, instead of fitting a single, high-degree polynomial to all of the values at once, spline interpolation fits low-degree polynomials to small subsets of the values, for example, fitting nine cubic polynomials between each of the pairs of ten points, instead of fitting a single degree-nine polynomial to all of ...

How does bilinear interpolation work? ›

The bilinear interpolation process uses the average of the data at each corner of the rectangle. The weights are based on the separation between the point and the corners for a (x,y) position inside the rectangle. The weight of the corner increases the closer it is to the tip.