Edge preserving interpolation of digital images using fuzzy inference

Abstract

This paper presents a novel edge preserving interpolation method for digital images. This new method reduces drastically the blurring and jaggy artifacts at the high-contrast edges, which are generally found in the interpolated images using conventional methods. This high performance is achieved by two proposed operations: a fuzzy-inference based edge preserving interpolator and a highly oblique edge compensation scheme developed based on an edge orientation detector. The former synthesizes the interpolated pixels to match the image local characteristics. Hence, edge sharpness can be retained. However, due to the small footage of the fuzzy interpolation method, it cannot avoid edge jaggedness along the highly oblique edges that have very sharp angles against one of the coordinates. Therefore, a segment matching technique is developed to identify precisely the orientation of the highly oblique edges. Combining these two techniques, we improve significantly the visual quality of the interpolated images, particularly at the high-contrast edges. Both the synthesized images (such as letters) and the natural scenes (captured by camera) have been tested and the results are very promising. (C) 1997 Academic Press.