{"title":"Simulation of non-line-of-sight imaging system based on the light-cone transform","authors":"Wenhua Zhu, J. Tan, Caiwen Ma, Xiuqin Su","doi":"10.1117/12.2586651","DOIUrl":null,"url":null,"abstract":"Non-line-of-sight (NLOS) imaging is an emerging technique, which can observe objects obscured by occluders. Thanks to the improvement of optical configurations, it is receiving growing interest from researchers. In this paper, we reconstruct both 2D and 3D images by adopting the light-cone transform and validated on simulated data. Numerical results are evaluated by structural similarity index (SSIM). The results showed the good performance of the algorithm in preserving the details of 2D image and reconstruction of 3D image. The structural similarity index of the reconstructed image and the reference image is more than 50%, the target is hence being identified. This work contributes to the construction of the real system.","PeriodicalId":370739,"journal":{"name":"International Conference on Photonics and Optical Engineering and the Annual West China Photonics Conference","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Photonics and Optical Engineering and the Annual West China Photonics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2586651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Non-line-of-sight (NLOS) imaging is an emerging technique, which can observe objects obscured by occluders. Thanks to the improvement of optical configurations, it is receiving growing interest from researchers. In this paper, we reconstruct both 2D and 3D images by adopting the light-cone transform and validated on simulated data. Numerical results are evaluated by structural similarity index (SSIM). The results showed the good performance of the algorithm in preserving the details of 2D image and reconstruction of 3D image. The structural similarity index of the reconstructed image and the reference image is more than 50%, the target is hence being identified. This work contributes to the construction of the real system.