Wavelet and footprint sampling of signals with a finite rate of innovation

Author

Dragotti, Pier Luigi ; Vetterli, Martin

Author_Institution

Electr. & Electron. Eng., Imperial Coll., London, UK

Volume

2

fYear

2004

fDate

17-21 May 2004

Abstract

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 (Dragotti, P.L. and Vetterli, M., IEEE Trans. Sig. Process., vol.51, no.5, p.1306-23, 2003). Preliminary results show the potentiality of this algorithm.

Keywords

signal reconstruction; signal resolution; signal sampling; wavelet transforms; Dirac streams; finite innovation rate; footprint sampling; multiresolution structure; piecewise polynomial signals; resolution enhancement algorithm; signal reconstruction; signal sampling; wavelet sampling; Discrete wavelet transforms; Educational institutions; Kernel; Polynomials; Sampling methods; Signal processing algorithms; Signal resolution; Signal sampling; Technological innovation; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on

ISSN

1520-6149

Print_ISBN

0-7803-8484-9

Type

conf

DOI

10.1109/ICASSP.2004.1326414

Filename

1326414