A hybrid Markov random field model for bilevel cutset reconstruction

Shengxin Zha, Thrasyvoulos N. Pappas

Abstract: We propose a hybrid Markov random field (MRF) model and a two stage cutset-MRF approach for reconstructing bilevel images from cutsets. We show that the proposed approach leads to substantial improvements over previous cutset-MRF approaches in terms of both reconstruction error and visual quality (continuity of reconstructed segments and preservation of image structure). The proposed approach approaches the performance of pattern-based approaches without the additional memory requirements and training overhead. We also show that it outperforms inpainting approaches adapted to bilevel cutset reconstruction.