期刊
OPTICS LETTERS
卷 47, 期 21, 页码 5461-5464出版社
Optica Publishing Group
DOI: 10.1364/OL.472680
关键词
-
类别
In this work, a novel sparse single-pixel imaging scheme and reconstruction algorithm are proposed to image target scenes at above 1K resolution with reduced measurements. Experimental results demonstrate the technique's superior accuracy and efficiency.
The speed of single-pixel imaging (SPI) is tied to its resolution, which is positively related to the number of modulation times. Therefore, efficient large-scale SPI is a serious challenge that impedes its wide applications. In this work, we report a novel, to the best of our knowledge, sparse SPI scheme and corresponding reconstruction algorithm to image target scenes at above 1 K resolution with reduced measurements. Specifically, we first analyze the statistical importance ranking of Fourier coefficients for natural images. Then the sparse sampling with a polynomially decending probability of the ranking is performed to cover a larger range of the Fourier spectrum than non-sparse sampling. The optimal sampling strategy with suitable sparsity is summarized for the best performance. Next, a lightweight deep distribution optimization ((DO)-O-2) algorithm is introduced for large-scale SPI reconstruction from sparsely sampled measurements instead of a conventional inverse Fourier transform (HT). The (DO)-O-2 algorithm empowers robustly recovering sharp scenes at 1 K resolution within 2 s. A series of experiments demonstrate the technique's superior accuracy and efficiency. (C) 2022 Optica Publishing Group
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据