One of the most common tasks in image processing is to change the resolution of a picture. In this paper we
present a new nonlinear method for interpolating digital images, which is particulary effective in the rendition of
edges in natural and synthetic input. The algorithm is spatial variant and applies the warped distance (WaDi)
concept, generalizing the technique to a two dimensional problem, which requires a non-separable approach.
It consists of three separate stages. First of all the original image is analyzed to detect its local gradient
characteristics; then edge asymmetry is computed at each output pixel position according to the WaDi technique,
and it is compared to a reference sigmoidal edge; the local edge asymmetry straightforwardly determines the
warping factor which is applied to the bi-dimensional space of the image; eventually the actual interpolation is
performed applying a conventional interpolator such as the linear or bicubic ones. The resulting interpolation
method gives an output which does not present the usual blurring typical of images processed with linear
interpolators and at the same time preserves the regularity of resized edges avoiding jagging artifacts. Moreover,
the method adapts for zooming by a rational scaling factor. The paper is organized as follows. In the first
section we introduce the problem of zooming digital images; the second section describes the state of the art; we
continue describing the proposed method; then we propose a possible extension of the method to process color
images; we end showing some examples of images interpolated with our method, and comparing these results
with what can be obtained zooming the same input with other interpolators.