A Hierarchical Wavelet-Based Framework for Pattern Analysis and Synthesis
| dc.citation.bibtexName | mastersthesis | en_US |
| dc.citation.journalTitle | Masters Thesis | en_US |
| dc.contributor.org | Center for Multimedia Communications (http://cmc.rice.edu/) | en_US |
| dc.creator | Scott, Clayton | |
| dc.date.accessioned | 2007-10-31T01:04:35Z | |
| dc.date.available | 2007-10-31T01:04:35Z | |
| dc.date.issued | 2000-04-20 | |
| dc.date.modified | 2003-07-12 | en_US |
| dc.date.submitted | 2002-10-30 | en_US |
| dc.description | Masters Thesis | en_US |
| dc.description.abstract | Despite their success in other areas of statsitical signal processing, current wavelet-based image models are inadequate for modeling patterns in images, due to the presence of unknown transformations inherent in most pattern observations. In this thesis we introduce a hierarchical wavelet-based framework for modeling patterns in digital images. This framework takes advantage of the efficient image representations afforded by wavelets, while accounting for unknown pattern transformations. Given a trained model, we can use this framework to synthesize pattern observations. If the model parameters are unknown, we can infer them from labeled training data using TEMPLAR, a novel template learning algorithm with linear complexity. TEMPLAR employs minimum description length (MDL) complexity regularization to learn a template with a sparse representation in the wavelet domain. If we are given several trained models for different patterns, our framework provides a low-dimensional subspace classifier that is invariant to unknown pattern transformations as well as background clutter. | en_US |
| dc.identifier.citation | "A Hierarchical Wavelet-Based Framework for Pattern Analysis and Synthesis," <i>Masters Thesis,</i> 2000. | |
| dc.identifier.uri | https://hdl.handle.net/1911/20339 | |
| dc.language.iso | eng | |
| dc.subject | Wavelets | * |
| dc.subject | pattern analysis | * |
| dc.subject | MDL | * |
| dc.subject.keyword | Wavelets | en_US |
| dc.subject.keyword | pattern analysis | en_US |
| dc.subject.keyword | MDL | en_US |
| dc.title | A Hierarchical Wavelet-Based Framework for Pattern Analysis and Synthesis | en_US |
| dc.type | Thesis | |
| dc.type.dcmi | Text | |
| thesis.degree.level | Masters |
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