access icon free Compressive sensing of images based on discrete periodic Radon transform

A new compressive sensing (CS) scheme using the structured random matrix and the discrete periodic Radon transform (DPRT) is proposed. The new scheme first pre-randomises the sensing image and the DPRT is applied to the randomised samples to generate the so-called DPRT projections. They are then randomly selected to obtain the final sensing measurements. As the DPRT is friendly to hardware/optics implementation, it improves the operability and lowers the cost for real-time CS applications. Compared with other similar transforms such as the Walsh–Hadamard transform, the proposed DPRT scheme gives much better reconstructed images as shown in the simulation results.

Inspec keywords: discrete Fourier transforms; compressed sensing; Radon transforms; random processes; matrix algebra

Other keywords: compressive sensing image scheme; randomised image samples; sensing measurements; discrete periodic Radon transform; hardware-optics implementation; structured random matrix; real-time CS applications; DPRT projection generation

Subjects: Other topics in statistics; Integral transforms; Algebra; Integral transforms; Optical, image and video signal processing; Other topics in statistics; Computer vision and image processing techniques

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2014.0770
Loading

Related content

content/journals/10.1049/el.2014.0770
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading