Presentation 2010-03-02
Sampling Theory for Signals with Finite Rate of Innovation and Application to Image Feature Extraction
Akira HIRABAYASHI, Pier-Luigi DRAGOTTI,
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Abstract(in English) We present a survey of sampling theory for signals with a finite rate of innovations, which is one of the current hot topics in sparse sampling as well as compressed sensing. We first show that rate of innovation is a notion which corresponds to frequency, and that signal with a finite rate of innovations is a natural extension of band-limited signal. To perfectly reconstruct such signals, sampling functions have to satisfy a reproducing characteristic of polynomials or exponential functions. This characteristic enables perfect reconstruction of a periodic stream of Diracs by using the so-called annihilating filter method. Based on this result, reconstruction methods for nonuniform splines and piecewise polynomial, or that in the presence of noise are derived. We also show, as an application to image processing, a line-edge extraction method based on these sampling techniques.
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Keyword(in English) Sparse sampling / signals with finite rate of innovation / spline functions / annihilating filter / image feature extraction
Paper # CAS2009-109,SIP2009-154,CS2009-104
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Committee CS
Conference Date 2010/2/22(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Sampling Theory for Signals with Finite Rate of Innovation and Application to Image Feature Extraction
Sub Title (in English)
Keyword(1) Sparse sampling
Keyword(2) signals with finite rate of innovation
Keyword(3) spline functions
Keyword(4) annihilating filter
Keyword(5) image feature extraction
1st Author's Name Akira HIRABAYASHI
1st Author's Affiliation Graduate School of Medicine, Yamaguchi University()
2nd Author's Name Pier-Luigi DRAGOTTI
2nd Author's Affiliation Faculty of Engineering, Imperial College London
Date 2010-03-02
Paper # CAS2009-109,SIP2009-154,CS2009-104
Volume (vol) vol.109
Number (no) 436
Page pp.pp.-
#Pages 6
Date of Issue