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Interpolation search is an algorithm for searching for a key in an array that has been ordered by numerical values assigned to the keys (key values).
The simplest interpolation method is to locate the nearest data value, and assign the same value. In simple problems, this method is unlikely to be used, as linear interpolation (see below) is almost as easy, but in higher-dimensional multivariate interpolation, this could be a favourable choice for its speed and simplicity.
The nearest neighbor algorithm selects the value of the nearest point and does not consider the values of neighboring points at all, yielding a piecewise-constant interpolant. [1] The algorithm is very simple to implement and is commonly used (usually along with mipmapping) in real-time 3D rendering [2] to select color values for a textured ...
For data requests that fall between the table's samples, an interpolation algorithm can generate reasonable approximations by averaging nearby samples." [ 8 ] In data analysis applications, such as image processing , a lookup table (LUT) can be used to transform the input data into a more desirable output format.
Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point. Closeness is typically expressed in terms of a dissimilarity function: the less similar the objects, the larger the function values.
Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...
Bicubic interpolation can be accomplished using either Lagrange polynomials, cubic splines, or cubic convolution algorithm. In image processing , bicubic interpolation is often chosen over bilinear or nearest-neighbor interpolation in image resampling , when speed is not an issue.
The computed interpolation process is then used to insert many new values in between these key points to give a "smoother" result. In its simplest form, this is the drawing of two-dimensional curves. The key points, placed by the artist, are used by the computer algorithm to form a smooth curve either through, or near these points.