Wiener crosses borders: interpolation based on second order models
Alvaro Guevara, Rudolf Mester · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Interpolation of signals (arbitrary dimension, here: 2D images) with missing data points is addressed from a statistical point of view. We present a general framework for which a Wiener-style MMSE estimator can be seamlessly adapted to deal with problems such as image interpolation (inpainting), reconstruction from sparse samples, and image extrapolation. The proposed method gives a precise answer on a) how arbitrary can linear filters can be applied to initially incomplete signals and b) shows the definite way to extend images beyond theirs borders such that no size reduction occurs if a linear filter/operator is to be applied to the image.