Interpolation of spatial data is a very general mathematical problem with various applications. In geostatistics, it is assumed that the underlying structure of the data is a stochastic process which leads to an interpolation procedure known as kriging. This method is mathematically equivalent to kernel interpolation, a method used in numerical analysis for the same problem, but derived under c...

Two forms of spatial interpolation, the interpolation of point and areal data, are distinguished. Traditionally, point interpolation is applied to isarithmic, that is, contour mapping and areal interpolation to isopleth mapping. Recently, areal interpolation techniques have been used to obtain data for a set of administrative or political districts from another set of districts whose boundaries...

where the infimum is taken over all pairs x^ÇzXj satisfying (2.1). One easily checks that (2.2) gives a norm on X 0 + X i when X0 and X% are compatible. Moreover, when X0+Xi is equipped with this norm, it becomes a Banach space (cf. [3]). Let Cfc denote the set of complex valued functions of the complex variable f = ̂ +irf which are continuous on bounded subsets of S, where fl is the strip 0 <£ ...

We discuss linear methods for interpolation, including nearest neighbor, bilinear, bicubic, splines, and sinc interpolation. We focus on separable interpolation, so most of what is said applies to one-dimensional interpolation as well as N-dimensional separable interpolation. Source Code The source code (ANSI C), its documentation, and the online demo are accessible at the IPOL web page of this...

Interpolation is the method of enlarging or stretching an image from a smaller original image to a larger resultant image. Whereas, Texture synthesis is the method of cleaning the image by using patches or pixels for making the image resolution higher and better than the original image. Here in this paper we have given an overview of different Interpolation and Texture Synthesis Methods. We hav...

A parametric class of modified B-spline functions is studied for its applicability in digital image interpolation tasks. The modified functions are generated by weighting and shifting of classical B-splines of different degrees. The weighting coefficients are optimized to assures an effective attenuation of the imaging frequencies, caused by the interpolation. The most computationally expensive...

We propose a new adaptive spatio-temporal interpolation method that combines either by a step or a line function existing spatial and temporal interpolation methods. We test the new method using climate data obtained from weather stations in Colorado and Nebraska, for the time period from 1993 to 2003. The experimental results show that in mountainous regions our adaptive spatio-temporal method...

To determine which interpolation technique is the most suitable for each case study an essential task a correct soil mapping, particularly in studies performed at regional scale. So, our main goal was to identify accurate method mapping 12 variables three different depth intervals: 0–5, 5–10 and &gt;10 cm. For doing that, we have compared nine methods (deterministic geostatistical), drawing map...