Pub Date : 2022-01-11DOI: 10.21203/rs.3.rs-1236950/v1
Huanyu Sun, Shiling Wang, Xiao-Xiang Hu, Hongjie Liu, Xiaoyan Zhou, Jin Huang, Xinglei Cheng, Feng Sun, Yubo Liu, Dong Liu
Surface defects (SDs) and subsurface defects (SSDs) are the key factors decreasing the laser damage threshold of optics. Due to the spatially stacked structure, accurately detecting and distinguishing them has become a major challenge. Herein a detection method for SDs and SSDs with multisensor image fusion is proposed. The optics is illuminated by a laser under dark field condition, and the defects are excited to generate scattering and fluorescence lights, which are received by two image sensors in a wide-field microscope. With the modified algorithms of image registration and feature-level fusion, different types of defects are identified and extracted from the scattering and fluorescence images. Experiments show that two imaging modes can be realized simultaneously by multisensor image fusion, and HF etching verifies that SDs and SSDs of polished optics can be accurately distinguished. This method provides a more targeted reference for the evaluation and control of the defects of optics, and exhibits potential in the application of material surface research.
{"title":"Detection of surface defects and subsurface defects of polished optics with multisensor image fusion","authors":"Huanyu Sun, Shiling Wang, Xiao-Xiang Hu, Hongjie Liu, Xiaoyan Zhou, Jin Huang, Xinglei Cheng, Feng Sun, Yubo Liu, Dong Liu","doi":"10.21203/rs.3.rs-1236950/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-1236950/v1","url":null,"abstract":"Surface defects (SDs) and subsurface defects (SSDs) are the key factors decreasing the laser damage threshold of optics. Due to the spatially stacked structure, accurately detecting and distinguishing them has become a major challenge. Herein a detection method for SDs and SSDs with multisensor image fusion is proposed. The optics is illuminated by a laser under dark field condition, and the defects are excited to generate scattering and fluorescence lights, which are received by two image sensors in a wide-field microscope. With the modified algorithms of image registration and feature-level fusion, different types of defects are identified and extracted from the scattering and fluorescence images. Experiments show that two imaging modes can be realized simultaneously by multisensor image fusion, and HF etching verifies that SDs and SSDs of polished optics can be accurately distinguished. This method provides a more targeted reference for the evaluation and control of the defects of optics, and exhibits potential in the application of material surface research.","PeriodicalId":93483,"journal":{"name":"PhotoniX","volume":" ","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47654335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-16DOI: 10.1186/s43074-021-00045-x
Chong Li, Xiang Zhang, Jingwei Li, Tao Fang, Xiaowen Dong
{"title":"Correction to: The challenges of modern computing and new opportunities for optics","authors":"Chong Li, Xiang Zhang, Jingwei Li, Tao Fang, Xiaowen Dong","doi":"10.1186/s43074-021-00045-x","DOIUrl":"https://doi.org/10.1186/s43074-021-00045-x","url":null,"abstract":"","PeriodicalId":93483,"journal":{"name":"PhotoniX","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48535565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-12DOI: 10.21203/RS.3.RS-599112/V1
Yao Fan, Jiaji Li, Linpeng Lu, Jiasong Sun, Yan Hu, Jialin Zhang, Zhuoshi Li, Qian Shen, Bowen Wang, Runnan Zhang, Qian Chen, C. Zuo
Computational microscopy, as a subfield of computational imaging, combines optical manipulation and image algorithmic reconstruction to recover multi-dimensional microscopic images or information of micro-objects. In recent years, the revolution in light-emitting diodes (LEDs), low-cost consumer image sensors, modern digital computers, and smartphones provide fertile opportunities for the rapid development of computational microscopy. Consequently, diverse forms of computational microscopy have been invented, including digital holographic microscopy (DHM), transport of intensity equation (TIE), differential phase contrast (DPC) microscopy, lens-free on-chip holography, and Fourier ptychographic microscopy (FPM). These computational microscopy techniques not only provide high-resolution, label-free, quantitative phase imaging capability but also decipher new and advanced biomedical research and industrial applications. Nevertheless, most computational microscopy techniques are still at an early stage of “proof of concept” or “proof of prototype” (based on commercially available microscope platforms). Translating those concepts to stand-alone optical instruments for practical use is an essential step for the promotion and adoption of computational microscopy by the wider bio-medicine, industry, and education community. In this paper, we present four smart computational light microscopes (SCLMs) developed by our laboratory, i.e., smart computational imaging laboratory (SCILab) of Nanjing University of Science and Technology (NJUST), China. These microscopes are empowered by advanced computational microscopy techniques, including digital holography, TIE, DPC, lensless holography, and FPM, which not only enables multi-modal contrast-enhanced observations for unstained specimens, but also can recover their three-dimensional profiles quantitatively. We introduce their basic principles, hardware configurations, reconstruction algorithms, and software design, quantify their imaging performance, and illustrate their typical applications for cell analysis, medical diagnosis, and microlens characterization.
{"title":"Smart computational light microscopes (SCLMs) of smart computational imaging laboratory (SCILab)","authors":"Yao Fan, Jiaji Li, Linpeng Lu, Jiasong Sun, Yan Hu, Jialin Zhang, Zhuoshi Li, Qian Shen, Bowen Wang, Runnan Zhang, Qian Chen, C. Zuo","doi":"10.21203/RS.3.RS-599112/V1","DOIUrl":"https://doi.org/10.21203/RS.3.RS-599112/V1","url":null,"abstract":"Computational microscopy, as a subfield of computational imaging, combines optical manipulation and image algorithmic reconstruction to recover multi-dimensional microscopic images or information of micro-objects. In recent years, the revolution in light-emitting diodes (LEDs), low-cost consumer image sensors, modern digital computers, and smartphones provide fertile opportunities for the rapid development of computational microscopy. Consequently, diverse forms of computational microscopy have been invented, including digital holographic microscopy (DHM), transport of intensity equation (TIE), differential phase contrast (DPC) microscopy, lens-free on-chip holography, and Fourier ptychographic microscopy (FPM). These computational microscopy techniques not only provide high-resolution, label-free, quantitative phase imaging capability but also decipher new and advanced biomedical research and industrial applications. Nevertheless, most computational microscopy techniques are still at an early stage of “proof of concept” or “proof of prototype” (based on commercially available microscope platforms). Translating those concepts to stand-alone optical instruments for practical use is an essential step for the promotion and adoption of computational microscopy by the wider bio-medicine, industry, and education community. In this paper, we present four smart computational light microscopes (SCLMs) developed by our laboratory, i.e., smart computational imaging laboratory (SCILab) of Nanjing University of Science and Technology (NJUST), China. These microscopes are empowered by advanced computational microscopy techniques, including digital holography, TIE, DPC, lensless holography, and FPM, which not only enables multi-modal contrast-enhanced observations for unstained specimens, but also can recover their three-dimensional profiles quantitatively. We introduce their basic principles, hardware configurations, reconstruction algorithms, and software design, quantify their imaging performance, and illustrate their typical applications for cell analysis, medical diagnosis, and microlens characterization.","PeriodicalId":93483,"journal":{"name":"PhotoniX","volume":"2 1","pages":"1-64"},"PeriodicalIF":0.0,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49543168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-13DOI: 10.1186/s43074-022-00070-4
Carlos R'ios, Qingyang Du, Yifei Zhang, C. Popescu, M. Shalaginov, P. Miller, Christopher M. Roberts, M. Kang, K. Richardson, T. Gu, S. Vitale, Juejun Hu
{"title":"Ultra-compact nonvolatile phase shifter based on electrically reprogrammable transparent phase change materials","authors":"Carlos R'ios, Qingyang Du, Yifei Zhang, C. Popescu, M. Shalaginov, P. Miller, Christopher M. Roberts, M. Kang, K. Richardson, T. Gu, S. Vitale, Juejun Hu","doi":"10.1186/s43074-022-00070-4","DOIUrl":"https://doi.org/10.1186/s43074-022-00070-4","url":null,"abstract":"","PeriodicalId":93483,"journal":{"name":"PhotoniX","volume":"3 1","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45264644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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