Bicubic interpolation

About: Bicubic interpolation is a research topic. Over the lifetime, 3348 publications have been published within this topic receiving 73126 citations.

Optimal interpolation of radiated fields over a sphere

Abstract: An optimal sampling interpolation algorithm is developed that allows the accurate recovery of scattered or radiated fields over a sphere from a minimum number of samples. Using the concept of the field equivalent (spatial) bandwidth, a central interpolation scheme is developed to compute the field in theta , phi coordinates, starting from its samples. The maximum allowable sample spacing and error upper bounds are also rigorously derived. Several simulated examples of pattern reconstruction are presented, for both the cases of field and power pattern interpolation. The interpolation error, as a function of the retained sample number, has been also evaluated and compared with the theoretical upper bounds. The algorithm stability versus randomly distributed errors added to the exact samples is demonstrated. >

Scattered data interpolation in three or more variables

Abstract: This is a survey of techniques for the interpolation of scattered data in three or more independent variables. It covers schemes that can be used for any number of variables as well as schemes specifically designed for three variables. Emphasis is on breadth rather than depth, but there are explicit illustrations of different techniques used in the solution of multivariate interpolation problems.

Comparison of Commonly Used Image Interpolation Methods

Abstract: Image magnification algorithms directly affect the quality of image magnification. In this paper, based on the image interpolation algorithm principle, features of the nearest neighbor interpolation, bilinear interpolation, bicubic interpolation and cubic B spline interpolation were analyzed. At the same time, their advantages and disadvantages were compared. In the experiment, image magnification performance of different interpolation algorithms was compared from subjective and objective aspects. The experimental results give the guidance for the user to choose a suitable algorithm to achieve optimum results according to different application. KeywordsImage magnification; Interpolation algorithm; Performance comparison

Linear Interpolation in Pilot Symbol Assisted Channel Estimation for OFDM

Abstract: In this paper, we investigate several efficient interpolation techniques for pilot symbol assisted channel estimation in OFDM. The interpolation methods studied include two dimensional (2-D) separable lowpass sine interpolator with Kaiser window, 2-D separable Deslauriers-Dubuc (DD) interpolation and 2-D discrete Fourier transform (DFT) based lowpass interpolation. The performances of these interpolators are compared with those of the well known minimum mean-square error (MMSE) 2-D separable Wiener filter and the perfect channel state information. It is shown that the Kaiser window based interpolator and DD interpolation are simple, robust, and outperform the 2-D DFT based lowpass interpolation as well as several existing interpolation methods proposed in the literature. These two schemes are suitable candidates for use in 1-D and 2-D channel estimation

Shape Preserving Piecewise Rational Interpolation

Abstract: An explicit representation of a $C^1 $ piecewise rational cubic function is developed which can be used to solve the problem of shape preserving interpolation. It is shown that the interpolation method can be applied to convex and/or monotonic sets of data and an error analysis of the interpolant is given. The scheme includes, as a special case, the monotonic rational quadratic interpolant considered by the authors in [1] and [5]. However, the requirement of convexity necessitates the generalization to the rational cubic form employed here.