Warped distance for space-variant linear image interpolation

The problem of image interpolation using linear techniques is dealt with in this paper. Conventional spaceinvariant methods are revisited and changed into space-variant ones, by introducing the concept of the warped distance among the pixels of an image. A better perceptual rendition of the image details is obtained in this way; this effect is proved both via the evaluation of the response to an idealized sigmoidal edge model and with experiments on real-world images. The computational costs of the proposed approach are very small when compared to those of state-of-the-art nonlinear interpolation operators.