Imaging using hyperuniform sampling with a single-pixel camera

Digital cameras use detector arrays with regular geometry for optical sampling. Though regular arrangement was demonstrated to be optimal for two-dimensional sampling, it causes aliasing at high frequencies exceeding its Nyquist limit. Here, we proposed a randomization procedure to generate 2D hyperuniform patterns that can be used to suppress aliasing in image retrieval. Experiments are performed using a single-pixel camera, where the sampling patterns do not necessarily follow a fixed Cartesian geometry. Results demonstrate that the images reconstructed by hyperuniform patterns have a lower root mean squared error and exhibit less moiré fringes at high frequencies than the images reconstructed by regular square patterns do. Furthermore, the same conclusion can be applied to the production of conventional detector arrays, where manufacturing imperfection could be utilized to suppress frequency aliasing in image retrieval.