@article {281, title = {Statistical fusion of two-scale images of porous media}, journal = {Advances in Water Resources}, volume = {32}, year = {2009}, pages = {1567 - 1579}, abstract = {

The reconstruction of the architecture of void space in porous media is a challenging task, since porous media contain pore structures at multiple scales. Whereas past methods have been limited to producing samples with matching statistical behavior, the patterns of grey-level values in a measured sample actually say something about the unresolved details, thus we propose a statistical fusion framework for reconstructing high-resolution porous media images from low-resolution measurements. The proposed framework is based on a posterior sampling approach in which information obtained by low-resolution (MRI or X-ray) measurements is combined with prior models inferred from high-resolution microscopic data, typically 2D. In this paper, we focus on two-scale reconstruction tasks in which the measurements resolve only the large scale structures, leaving the small-scale to be inferred. The evaluation of the results generated by the proposed method shows the strong ability of the proposed method in reconstructing fine-scale structures positively correlated with the underlying ground truth. Comparing our method with the recent method of Okabe and Blunt [12], in which the measurements are also used in the reconstruction, we conclude that our method is more robust to the resolution of the measurement, and more closely matches the underlying fine-scale field.

}, keywords = {Data fusion, magnetic resonance imaging, Porous media reconstruction, Posterior sampling, simulated annealing}, issn = {0309-1708}, doi = {http://dx.doi.org/10.1016/j.advwatres.2009.08.005}, url = {http://www.sciencedirect.com/science/article/pii/S0309170809001274}, author = {A Mohebi and P Fieguth and M A. Ioannidis} } @inproceedings {340, title = {Statistical fusion and sampling of scientific images}, booktitle = {15th IEEE International Conference on Image Processing}, year = {2008}, abstract = {

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.
}, keywords = {artificial samples, complex random structures, heterogeneous materials possessing, image fusion, image reconstruction, image resolution, image sampling, low resolution measurements, porous media, Posterior sampling, scientific image sampling, statistical analysis, statistical fusion approach, two-scale porous media reconstruction, two-scale reconstruction}, doi = {http://dx.doi.org/10.1109/ICIP.2008.4712004}, author = {A Mohebi and P Fieguth} }