Image Interpolation with Geometric Contour Stencils
Pascal Getreuer
→ BibTeX
    title   = {{Image Interpolation with Geometric Contour Stencils}},
    author  = {Getreuer, Pascal},
    journal = {{Image Processing On Line}},
    volume  = {1},
    pages   = {98--116},
    year    = {2011},
    doi     = {10.5201/ipol.2011.g_igcs},
% if your bibliography style doesn't support doi fields:
    note    = {\url{}}
Pascal Getreuer, Image Interpolation with Geometric Contour Stencils, Image Processing On Line, 1 (2011), pp. 98–116.

Communicated by Gabriele Facciolo
Demo edited by Pascal Getreuer

This IPOL article is related to a companion publication in the SIAM Journal on Imaging Sciences:
P. Getreuer. "Contour Stencils: Total Variation along Curves for Adaptive Image Interpolation." SIAM Journal on Imaging Sciences, vol. 4, no. 3, pp. 954--979, 2011.


We consider the image interpolation problem where given an image vm,n with uniformly-sampled pixels vm,n and point spread function h, the goal is to find function u(x,y) satisfying vm,n = (h*u)(m,n) for all m,n in Z.

This article improves upon the IPOL article Image Interpolation with Contour Stencils. In the previous work, contour stencils are used to estimate the image contours locally as short line segments. This article begins with a continuous formulation of total variation integrated over a collection of curves and defines contour stencils as a consistent discretization. This discretization is more reliable than the previous approach and can effectively distinguish contours that are locally shaped like lines, curves, corners, and circles. These improved contour stencils sense more of the geometry in the image.

Interpolation is performed using an extension of the method described in the previous article. Using the improved contour stencils, there is an increase in image quality while maintaining similar computational efficiency.