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.

Date Published: 19 January 2009
PDF: 13 pages
Proc. SPIE 7257, Visual Communications and Image Processing 2009, 725718 (19 January 2009); doi: 10.1117/12.806014

Published in SPIE Proceedings Vol. 7257:
Visual Communications and Image Processing 2009
Majid Rabbani; Robert L. Stevenson, Editor(s)