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dc.contributor.authorCampaigne, Wesley
dc.date.accessioned2012-06-21 19:50:18 (GMT)
dc.date.available2012-06-21 19:50:18 (GMT)
dc.date.issued2012-06-21T19:50:18Z
dc.date.submitted2012
dc.identifier.urihttp://hdl.handle.net/10012/6810
dc.description.abstractThere is significant interest in the synthesis of discrete-state random fields, particularly those possessing structure over a wide range of scales. However, given a model on some finest, pixellated scale, it is computationally very difficult to synthesize both large and small-scale structures, motivating research into hierarchical methods. This thesis proposes a frozen-state approach to hierarchical modelling, in which simulated annealing is performed on each scale, constrained by the state estimates at the parent scale. The approach leads significant advantages in both modelling flexibility and computational complexity. In particular, a complex structure can be realized with very simple, local, scale-dependent models, and by constraining the domain to be annealed at finer scales to only the uncertain portions of coarser scales, the approach leads to huge improvements in computational complexity. Results are shown for synthesis problems in porous media.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectsimulated annealingen
dc.subjectimage synthesisen
dc.subjectrandom fieldsen
dc.titleFrozen-State Hierarchical Annealingen
dc.typeMaster Thesisen
dc.pendingfalseen
dc.subject.programSystem Design Engineeringen
uws-etd.degree.departmentSystems Design Engineeringen
uws-etd.degreeMaster of Applied Scienceen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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