In any problem involving images having scale-dependent structures, a key issue is the modeling of these multi-scale characteristics. Because multi-scale phenomena frequently possess nonstationary, piece-wise multi-model behaviour, the classic hidden Markov method can not perform well in modeling such complex images. In this paper we provide a new modeling approach to extend previous hierarchical methods, with multiple hidden fields, to perform reconstruction in more complex, nonstationary contexts. © 2009 Springer.
CITATION STYLE
Liu, Y., & Fieguth, P. (2009). Parallel hidden hierarchical fields for multi-scale reconstruction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5681 LNCS, pp. 70–83). https://doi.org/10.1007/978-3-642-03641-5_6
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