Name
Abstract | ||
|---|---|---|
With the advent of a single-pixel camera, compressive imaging applications have gained wide interests. However, the design of efficient measurement basis in such a system remains as a challenging problem. In this paper, we propose a highly sparse and fast sampling operator based on the scrambled block Hadamard ensemble. Despite its simplicity, the proposed measurement operator offers universality and requires a near-optimal number of samples for perfect reconstruction. Moreover, it can be easily implemented in the optical domain thanks to its integer-valued elements. Several numerical experiments show that its imaging performance is comparable to that of the dense, floating-coefficient scrambled Fourier ensemble at much lower implementation cost. |
Year | Venue | Field |
|---|---|---|
2008 | European Signal Processing Conference | Algorithm,Theoretical computer science,Fourier transform,Sampling (statistics),Operator (computer programming),Universality (philosophy),Hadamard transform,Compressed sensing,Mathematics |
DocType | ISSN | Citations |
Conference | 2219-5491 | 61 |
PageRank | References | Authors |
2.59 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lu Gan | 1 | 96 | 6.31 |
| Thong T. Do | 2 | 234 | 12.76 |
| Trac D. Tran | 3 | 1507 | 108.22 |