国内紫外像增强器视场瑕疵检测技术研究现状  

Research Status of Local Defect Detection Technology of Ultraviolet Image Intensifier Field of View

作　　者：丁习文 程宏昌 袁渊 张若愚 杨书宁 杨晔 党小刚 DING Xiwen;CHENG Hongchang;YUAN Yuan;ZHANG Ruoyu;YANG Shuning;YANG Ye;DANG Xiaogang(Kunming Physics Research Institute,Kunming 650223,China;Key Laboratory of Low-Light-Level Night Vision Technology,Xi'an 710065,China)

机构地区：[1]昆明物理研究所,云南昆明650223 [2]微光夜视技术重点实验室,陕西西安710065

出　　处：《红外技术》2024年第2期129-137,共9页Infrared Technology

摘　　要：紫外像增强器是一种对紫外辐射敏感的成像器件,视场瑕疵是其成像效果的主要制约因素。目前,视场瑕疵检测技术主要分为人工和机器视觉两种方法。本文首先阐述了视场瑕疵的定义和检测标准。接着从瑕疵交叠靠近、大小和数量特性的角度,分析了视场瑕疵检测的难点。随后,重点介绍了紫外像增强器视场瑕疵检测技术的研究现状。结合当前的检测需求和不足,调研了深度学习技术在其他领域的瑕疵检测效果。最后,从理论上进行了可行性分析,并提出了基于深度学习视场瑕疵检测的思路,旨在为紫外像增强器视场瑕疵检测提供一种新的解决方案,推动其向着更加实用、智能化的方向发展。Ultraviolet image intensifiers are imaging devices that are sensitive to ultraviolet radiation.Defects in the field of view are the main factors restricting the imaging effect of ultraviolet image intensifiers.Currently,the field-of-view defect detection technology is mainly divided into artificial and machine vision.This paper explains the definitions and detection standards for field defects.Subsequently,the difficulties in field defect detection are analyzed from the perspectives of defect-overlapping proximity,size,and quantity.Next,the research status of the field-of-view defect detection technology of ultraviolet image intensifiers is introduced.Combined with the current detection requirements and deficiencies,the defect detection effect of deep-learning technology in other fields was investigated.Finally,a theoretical feasibility analysis is presented,and the concept of field defect detection based on deep learning is proposed.The purpose is to provide a new solution for field defect detection of ultraviolet image intensifiers and promote their development in a practical and intelligent direction.

关 键 词：像增强器 视场瑕疵检测 机器视觉 深度学习 

分 类 号：TN23[电子电信—物理电子学] TP391.4[自动化与计算机技术—计算机应用技术]