Morphological image interpolation to magnify images with sharp edges

Authors:
Valérie De Witte;Stefan Schulte;Etienne E. Kerre;Alessandro Ledda;Wilfried Philips
Affiliations:
Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Gent, Belgium;Telin Department, IPI Group, Gent, Belgium;Telin Department, IPI Group, Gent, Belgium
Venue:
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Year:
2006

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Abstract

In this paper we present an image interpolation method, based on mathematical morphology, to magnify images with sharp edges. Whereas a simple blow up of the image will introduce jagged edges, called ‘jaggies’, our method avoids these jaggies, by first detecting jagged edges in the trivial nearest neighbour interpolated image, making use of the hit-or-miss transformation, so that the edges become smoother. Experiments have shown that our method performs very well for the interpolation of ‘sharp’ images, like logos, cartoons and maps, for binary images and colour images with a restricted number of colours.