@inproceedings {297,
	title = {Image resolution enhancement with hierarchical hidden fields},
	booktitle = {6th International Conference on Image Analysis and Recognition},
	year = {2009},
	abstract = {<p>In any image processing involving images having scale-dependent structure, a key challenge is the modeling of these multi-scale characteristics. Because single Gauss-Markov models are effective at representing only single-scale phenomena, the classic Hidden Markov Model can not perform well in the processing of more complex images, particularly near-fractal images which frequently occur in scientific imaging. Of further interest is the presence of space-variable, nonstationary behaviour. By constructing hierarchical hidden fields, which label the behaviour type, we are able to capture heterogeneous structure in a scale-dependent way. We will illustrate the approach with a method of frozen-state simulated annealing and will apply it to the resolution enhancement of porous media images.</p>
},
	isbn = {978-3-642-02610-2},
	doi = {http://dx.doi.org/10.1007/978-3-642-02611-9_8},
	author = {Y Liu and P Fieguth}
}
