Tang Zixin, Tang Tianhang, Shi Xuelei, Chen Jie, Liu Yiguang
Opt Lett. 2022 Mar 1;47(5):1218-1221. doi: 10.1364/OL.448658.
The imaging quality of the conventional single-pixel-imaging (SPI) technique seriously degrades at a low sampling rate. To tackle this problem, we propose an efficient sampling method and a high-quality real-time image reconstruction strategy: first, different from the conventional simple circular path sampling strategy or variable density random sampling technique, the proposed method samples the Fourier spectrum using the spectrum distribution of the image, that is, sampling the significant spectrum coefficients first, which will help to improve the image quality at a relevantly low sampling rate; second, to handle the long image reconstruction time caused by the iterative algorithm, the sparsity of the image and the alternating direction optimization strategy are combined to ameliorate the reconstruction process in the image gradient space. Compared with the state-of-the-art techniques, the proposed method significantly improves the imaging quality and achieves real-time reconstruction on the time scale of milliseconds.
传统单像素成像（SPI）技术在低采样率下成像质量会严重下降。为解决这一问题，我们提出了一种高效采样方法和高质量实时图像重建策略：首先，与传统的简单圆形路径采样策略或变密度随机采样技术不同，该方法利用图像的频谱分布对傅里叶频谱进行采样，即先对重要的频谱系数进行采样，这有助于在较低采样率下提高图像质量；其次，为处理迭代算法导致的图像重建时间长的问题，将图像的稀疏性与交替方向优化策略相结合，以改善图像梯度空间中的重建过程。与现有技术相比，该方法显著提高了成像质量，并在毫秒级时间尺度上实现了实时重建。
