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Linear Methods for Image Interpolation

Reference P. Getreuer, “Linear Methods for Image Interpolation.” Image Processing On Line, 2011. DOI: 10.5201/ipol.2011.g_lmii.
Permalink http://dx.doi.org/10.5201/ipol.2011.g_lmii
Bibtex
@article{getreuer11linear,
    title = {Linear Methods for Image Interpolation},
    author = {Pascal Getreuer},
    journal = {Image Processing On Line},
    year = {2011},
    doi = {10.5201/ipol.2011.g_lmii},
}
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Abstract
Given input image v with uniformly-sampled pixels vm,n, the goal of interpolation is to find a function u(x,y) satisfying

vm,n = u(m,n)    for all integer m,n,

such that u approximates the underlying function from which v was sampled. Another way to interpret this is v was created by subsampling, and interpolation attempts to invert this process. 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.

©2011, IPOL Image Processing On Line & the authors.