Open AccessCompressive sensing of images based on discrete periodic Radon transform
Author(s) -
Ou G.W.,
Lun D.P.K.,
Ling B.W.K.
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.0770
Subject(s) - hadamard transform , compressed sensing , radon transform , radon , operability , algorithm , computer science , image (mathematics) , iterative reconstruction , matrix (chemical analysis) , scheme (mathematics) , computer vision , mathematics , physics , materials science , mathematical analysis , software engineering , quantum mechanics , composite material
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.