Single pixel imaging via sparse projection angle sampling

The recently proposed Radon single pixel imaging (RSPI) is based on Radon transform and considered to be a prospective technique in many fields, such as computed tomography, feature detection, classification and so on. And because of the fact that the exact implementation of inverse discrete Radon transformation does not exist, an approximate algorithm, filtered back projection, is employed to reconstruct the result images in RSPI. However, the presence of disturbing streak artifacts emerging from high-contrast structures hinders the high-quality reconstructions, especially at low sampling rates. In order to get rid of this dilemma, a novel single pixel imaging technique, which employs a few projection angle patterns to achieve sparse projection angle sampling and utilizes compressive sensing to reconstruct the result images, is proposed. Simulation and experimental results demonstrate that the image quality reconstructed by the proposed technique is much higher than that of RSPI at low sampling rates. Additionally, the proposed technique also has advantages in a lot of fields such as tomographic reconstruction at low radiation.