NDLI: Recovering filamentary objects in severely degraded binary images using beamlet-driven partitioning

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Optimum leakage factor for the MOV-LMS algorithm in nonlinear modeling and control systems

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Adaptive update lifting with gradient criteria modeling high-order differences

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EM algorithm applied to non-stationary noisy phase signals

Wigner-Ville and polynomial Wigner-Ville Transforms in the estimation of nonlinear FM signal parameters

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Theory of higher-order Rihaczek spectra

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2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)

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Recovering filamentary objects in severely degraded binary images using beamlet-driven partitioning

Content Provider	IEEE Xplore Digital Library
Author	Huo, Xiaoming Donoho, David
Copyright Year	2002
Description	Author affiliation: Department of Statistics, Stanford University, CA 94305, USA (Donoho, David) \|\| School of ISyE, Georgia Institute of Technology, Atlanta, 30332, USA (Huo, Xiaoming)
Abstract	We consider the problem of recovering a binary image consisting of many filaments or linear fragments in the presence of severe binary noise. Our approach exploits beamlets—a dyadically organized, multiscale system of line segments—and associated fast algorithms for beamlet analysis. It considers models based on beamlet-decorated recursive dyadic partitions, and models the image as a Bernoulli random process with spatially variant success probability, which is “high” within the beamlet complexity-penalized model fitting. Simulation results demonstrate the effectiveness of the method.
File Size	676251
File Format	PDF
ISBN	0780374029
ISSN	15206149
DOI	10.1109/ICASSP.2002.5744032
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-05-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pixel Fuses Educational institutions
Content Type	Text
Resource Type	Article

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