Image Interpolation with Geometric Contour Stencils

We consider the image interpolation problem where, given an image v with uniformly-sampled pixels vm,n and point spread function h, the goal is to find a function u(x, y) satisfying vm,n = (h ∗ u)(m,n) for all m,n ∈ Z (1) so that u approximates the underlying function from which v was sampled. This article improves upon the IPOL article “Image Interpolation with Contour Stencils” [7]. 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. Source Code ANSI C source code to produce the same results as the demo is accessible on the article web page http://dx.doi.org/10.5201/ipol.2011.g_igcs. Future software releases and updates will be posted at http://dev.ipol.im/~getreuer/code.