Optimal face reconstruction using training

In previous work Muresan and Parks (see ICIP 2001, Greece, 2001) considered the problem of image interpolation from an adaptive optimal recovery point of view. They showed how a training set S determines a quadratic signal class and how to use this signal class to perform image interpolation. In that work the training set S was taken from the low resolution version of the image they were interpolating. In this paper we continue our discussion of the method presented previously by looking more closely at the training set S. In particular, we show how a training set of high resolution images can give very good interpolation results through the use of the method.