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dc.contributor.authorScott, Clayton
Nowak, Robert David
dc.creatorScott, Clayton
Nowak, Robert David 2007-10-31T01:04:41Z 2007-10-31T01:04:41Z 2001-04-20 2001-04-20
dc.description Conference Paper
dc.description.abstract Despite the success of wavelet decompositions in other areas of statistical signal and image processing, current wavelet-based image models are inadequate for modeling patterns in images, due to the presence of unknown transformations (e.g., translation, rotation, location of lighting source) inherent in most pattern observations. In this paper 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 (Template Learning from Atomic Representations), 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. We discuss several applications, including template learning, pattern classification, and image registration.
dc.language.iso eng
pattern analysis
supervised learning
dc.subject.otherImage Processing and Pattern analysis
dc.title TEMPLAR: A Wavelet-Based Framework for Pattern Learning and Analysis
dc.type Conference paper 2004-01-09
dc.citation.bibtexName inproceedings 2004-01-09
dc.contributor.orgDigital Signal Processing (
pattern analysis
supervised learning
dc.citation.conferenceName IEEE Transactions on Signal Processing
dc.type.dcmi Text
dc.type.dcmi Text
dc.identifier.citation C. Scott and R. D. Nowak, "TEMPLAR: A Wavelet-Based Framework for Pattern Learning and Analysis," 2001.

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  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • ECE Publications [1305]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students

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