Maximum a posteriori image restoration based on a new directional continuous edge image prior

In this paper we propose a new hierarchical non stationary image prior for image restoration. This prior captures the directional edges using a continuous model and regularizes accordingly the restored images. In addition, the corresponding generative graphical model does not contain cycles, thus learning this model is easy and fast. Based on this prior image model, a maximum a posteriori (MAP) estimation algorithm is derived. Numerical experiments are provided that demonstrate the advantages of the proposed non stationary model as compared with algorithms that use stationary models. Keywords-(Image restoration, non-staionary prior, maximum a posteriori estimation, spatially adaptive regularization.)

• Type: Conference
• Year: 2005
• Where: ICIP
• Authors: John Chantas, Nikolas P. Galatsanos, Aristidis Likas
• Keywords: Generative Graphical Model, ICIP 2005, Image Processing, Non Stationary Image, Non Stationary Model, Posteriori Estimation, Prior Image Model