Ghost Imaging with Deep Learning for Position Mapping of Weakly Scattered Light Source

• 作者: Yasuhiro Mizutani Shoma Kataoka Tsutomu Uenohara YasuhiroTakaya
• 来源期刊: 纳米制造与计量(英文)
• 学科: 工学
• 关键词: Inspection METROLOGY Defect mapping Ghost imaging Single-pixel imaging Deep learning Weak light imaging
• 年，卷（期）: 2021,（1）
• 页码范围: 37-45
• 页数: 9页
• 分类号: TP3

摘要

We propose ghost imaging(GI)with deep learning to improve detection speed.GI,which uses an illumination light with random patterns and a single-pixel detector,is correlation-based and thus suitable for detecting weak light.However,its detection time is too long for practical inspection.To overcome this problem,we applied a convolutional neural network that was constructed based on a classification of the causes of ghost image degradation.A feasibility experiment showed that when using a digital mirror device projector and a photodiode,the proposed method improved the quality of ghost images.