|Title||Hierarchical MCMC sampling|
|Publication Type||Conference Paper|
|Year of Publication||2004|
|Conference Name||2004 International Conference on Image Analysis and Recognition|
We maintain that the analysis and synthesis of random fields is much faster in a hierarchical setting. In particular, complicated long-range interactions at a fine scale become progressively more local (and therefore more efficient) at coarser levels. The key to effective coarse-scale activity is the proper model definition at those scales. This can be difficult for locally-coupled models such as Ising, but is inherent and easy for those models, commonly used in porous media, which express constraints in terms of lengths and areas.