Statistical fusion and sampling of scientific images
Porous media are an important class of heterogeneous materials possessing complex random structures. Due to the limitation in measuring high resolution real samples, studying different physical properties of porous media requires the reconstruction of artificial samples. In many cases of significant interest, we have a two-scale reconstruction, in which only the large scales are resolved by low resolution measurements, leaving fine scales to be inferred from statistical models. In this paper we propose a statistical fusion approach for a two-scale porous media reconstruction, in which low resolution measurements are fused with high resolution samples, with synthetic realizations generated by posterior sampling.