Resolution enhancement and sampling with wavelets and footprints | Zendy

Pier Luigi Dragotti | Zendy; Martin Vetterli | Zendy

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Resolution enhancement and sampling with wavelets and footprints

Author(s) -

Pier Luigi Dragotti,

Martin Vetterli

Publication year - 2003

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.504724

Subject(s) - wavelet , bandlimiting , computer science , sampling (signal processing) , piecewise , algorithm , kernel (algebra) , noise (video) , multiresolution analysis , discrete wavelet transform , wavelet transform , artificial intelligence , fourier transform , computer vision , mathematics , mathematical analysis , combinatorics , filter (signal processing) , image (mathematics)

In this paper, we consider classes of not bandlimited signals, namely, streams of Diracs and piecewise polynomial signals, and show that these signals can be sampled and perfectly reconstructed using wavelets as sampling kernel. Due to the multiresolution structure of the wavelet transform, these new sampling theorems naturally lead to the development of a new resolution enhancement algorithm based on wavelet footprints.2 Preliminary results show that this algorithm is also very resilient to noise.

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