Multivariate interpolation | Signal processing

Lanczos resampling

Lanczos filtering and Lanczos resampling are two applications of a mathematical formula. It can be used as a low-pass filter or used to smoothly interpolate the value of a digital signal between its samples. In the latter case it maps each sample of the given signal to a translated and scaled copy of the Lanczos kernel, which is a sinc function windowed by the central lobe of a second, longer, sinc function. The sum of these translated and scaled kernels is then evaluated at the desired points. Lanczos resampling is typically used to increase the sampling rate of a digital signal, or to shift it by a fraction of the sampling interval. It is often used also for multivariate interpolation, for example to resize or rotate a digital image. It has been considered the "best compromise" among several simple filters for this purpose. The filter is named after its inventor, Cornelius Lanczos (Hungarian pronunciation: [ˈlaːnt͡soʃ]). (Wikipedia).

Lanczos resampling
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Related pages

Support (mathematics) | Gibbs phenomenon | Low-pass filter | Window function | Clipping (signal processing) | Derivative | Nearest-neighbor interpolation | Fourier series | Bilinear interpolation | Continuous function | Interpolation | Cornelius Lanczos | Aliasing | Multivariate interpolation | Spline interpolation | Ringing artifacts | Signal reconstruction | Digital image | Bicubic interpolation | Sinc filter | Sinc function | Partition of unity | Convolution