Spectrum-blind minimum-rate sampling and reconstruction of 2-D multiband signals

Yoram Bresler, Ping Feng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider 2-D multiband signals, with a given bound on their spectral occupancy (the occupied fraction of the area of a bounding box of the spectral support). We propose a universal sampling pattern that guarantees well-conditioned reconstruction of all such signals. Such a universal sampling pattern can asymptotically achieve the Nyquist-Landau minimal sampling rate, determined by the spectral occupancy. Compared to `Nyquist' patterns that avoid aliasing, for sparse spectral supports our design offers considerable reduction in sampling rate. Furthermore, we propose algorithms allowing reconstruction to be done blindly - without prior knowledge of the spectral support, other than its bounding box. The results apply to both continuous and discrete-time signals, and directly generalize to M-D. This work extends our analogous recent results for the 1D case.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
Editors Anon
PublisherIEEE
Pages701-704
Number of pages4
Volume1
StatePublished - 1996
EventProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz
Duration: Sep 16 1996Sep 19 1996

Other

OtherProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3)
CityLausanne, Switz
Period9/16/969/19/96

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Spectrum-blind minimum-rate sampling and reconstruction of 2-D multiband signals'. Together they form a unique fingerprint.

Cite this