Opt Lett. 2018 Aug 15;43(16):4049-4052. doi: 10.1364/OL.43.004049.
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.
数字相机使用具有规则几何形状的探测器阵列进行光学采样。虽然规则排列被证明是二维采样的最佳选择，但它会在超过奈奎斯特极限的高频处产生混叠。在这里，我们提出了一种随机化程序来生成二维超均匀图案，可用于抑制图像检索中的混叠。实验使用单像素相机进行，其中采样图案不一定遵循固定的笛卡尔几何形状。结果表明，由超均匀图案重建的图像具有更低的均方根误差，并且在高频处比由规则正方形图案重建的图像具有更少的莫尔条纹。此外，该结论也适用于常规探测器阵列的制作，其中制造缺陷可用于抑制图像检索中的频率混叠。
