A non-iterative foveated single-pixel imaging using fast transformation algorithm

Abstract

Inspired by the human eye retina, foveated single-pixel imaging employs an iterative algorithm, which, unfortunately, poses a challenge for real-time imaging due to its time-consuming nature. To address this issue, we present a non-iterative foveated single-pixel imaging method based on a computationally fast algorithm, reducing time consumption by five orders of magnitude. The fast algorithmic transform facilitates the acquisition of foveated reconstructions. In addition to mimicking human saccadic eye movements, the foveated strategy adapts to motion tracking through the foveal gaze control method. During high-resolution imaging in the fovea area, the maximum sensing area expands 3.14 times, similar to human vision. The proposed retina-like single-pixel imaging has great potential in future applications with the advantages of avoiding complex optics design, low time consumption, and wider vision field.