自相关
斑点图案
光学
相位恢复
散射
计算机科学
自相关技术
散斑噪声
航程(航空)
人工智能
算法
物理
材料科学
数学
傅里叶变换
统计
量子力学
复合材料
作者
da lu,Yuanyue Feng,Xiang Peng,Wenqi He
出处
期刊:Optics Express
[The Optical Society]
日期:2023-02-08
卷期号:31 (4): 6529-6529
被引量:2
摘要
Imaging through scattering media remains a big challenge in optics while the single-shot non-invasive speckle autocorrelation technique (SAT) is well-known as a promising way to handle it. However, it usually cannot recover a large-scale target or multiple isolated small ones due to the limited effective range of the optical memory effect (OME). In this paper, we propose a multi-target scattering imaging scheme by combining the traditional SA algorithm with a Deep Learning (DL) strategy. The basic idea is to extract each autocorrelation component of every target from the autocorrelation result of a mixed speckle using a suitable DL method. Once we get all the expected autocorrelation components, a typical phase retrieval algorithm (PRA) could be applied to reveal the shapes of all those corresponding small targets. In our experimental demonstration, up to five isolated targets are successfully recovered.
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