Contour stencils for edge-adaptive image interpolation

We first develop a simple method for detecting the local orientation of image contours and then use this detection to design an edge-adaptive image interpolation strategy. The detection is based on total variation: small total variation along a candidate curve implies that the image is approximately constant along that curve, which suggests it is a good approximation to the contours. The proposed strategy is to measure the total variation over a "contour stencil," a set of parallel curves localized over a small patch in the image. This contour stencil detection is used to design an edge-adaptive image interpolation strategy. The interpolation is computationally efficient, operates robustly over a variety of image features, and performs competitively in a comparison against existing methods. The method extends readily to vector-valued data and is demonstrated for color image interpolation. Other applications of contour stencils are also discussed.

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