Abstract
We address the problem of sampling of 2D signals with sparse multi-band spectral structure. We show that the signal can be sampled at a fraction of the its Nyquist density determined by the occupancy of the signal in its frequency domain, but without explicit knowledge of its spectral structure. We find that such a signal can almost surely be reconstructed from its multi-coset samples provided that a universal pattern is used. Also, the scheme can attain the Landau-Nyquist minimum density asymptotically. The spectrum blind feature of our reconstruction scheme has potential applications in Fourier imaging. We apply the sampling scheme on a test image to demonstrate its performance.
Original language | English (US) |
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Title of host publication | IEEE International Conference on Image Processing |
Publisher | IEEE Comp Soc |
Pages | 752-756 |
Number of pages | 5 |
Volume | 2 |
State | Published - 1998 |
Event | Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA Duration: Oct 4 1998 → Oct 7 1998 |
Other
Other | Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) |
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City | Chicago, IL, USA |
Period | 10/4/98 → 10/7/98 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Hardware and Architecture
- Electrical and Electronic Engineering