{"title":"无透镜成像的编码照明和多路复用","authors":"Yucheng Zheng, Rongjia Zhang, M. Salman Asif","doi":"10.1109/ICASSP40776.2020.9052955","DOIUrl":null,"url":null,"abstract":"Mask-based lensless cameras offer an alternative option to conventional cameras. Compared to conventional cameras, lensless cameras can be extremely thin, flexible, and lightweight. Despite these advantages, the quality of images recovered from the lensless cameras is often poor because of the ill-conditioning of the underlying linear system. In this paper, we propose a new method to address the problem of illconditioning by combining coded illumination patterns with the mask-based lensless imaging. We assume that the object is illuminated with multiple binary patterns and the camera acquires a sequence of images for different illumination patterns. We propose a low-complexity, recursive algorithm that avoids storing all the images or creating a large system matrix. We present simulation results on standard test images under various extreme conditions and demonstrate that the quality of the image improves significantly with a small number of illumination patterns.","PeriodicalId":13127,"journal":{"name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"74 1","pages":"9250-9253"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Coded Illumination and Multiplexing for Lensless Imaging\",\"authors\":\"Yucheng Zheng, Rongjia Zhang, M. Salman Asif\",\"doi\":\"10.1109/ICASSP40776.2020.9052955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mask-based lensless cameras offer an alternative option to conventional cameras. Compared to conventional cameras, lensless cameras can be extremely thin, flexible, and lightweight. Despite these advantages, the quality of images recovered from the lensless cameras is often poor because of the ill-conditioning of the underlying linear system. In this paper, we propose a new method to address the problem of illconditioning by combining coded illumination patterns with the mask-based lensless imaging. We assume that the object is illuminated with multiple binary patterns and the camera acquires a sequence of images for different illumination patterns. We propose a low-complexity, recursive algorithm that avoids storing all the images or creating a large system matrix. We present simulation results on standard test images under various extreme conditions and demonstrate that the quality of the image improves significantly with a small number of illumination patterns.\",\"PeriodicalId\":13127,\"journal\":{\"name\":\"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"volume\":\"74 1\",\"pages\":\"9250-9253\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP40776.2020.9052955\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP40776.2020.9052955","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coded Illumination and Multiplexing for Lensless Imaging
Mask-based lensless cameras offer an alternative option to conventional cameras. Compared to conventional cameras, lensless cameras can be extremely thin, flexible, and lightweight. Despite these advantages, the quality of images recovered from the lensless cameras is often poor because of the ill-conditioning of the underlying linear system. In this paper, we propose a new method to address the problem of illconditioning by combining coded illumination patterns with the mask-based lensless imaging. We assume that the object is illuminated with multiple binary patterns and the camera acquires a sequence of images for different illumination patterns. We propose a low-complexity, recursive algorithm that avoids storing all the images or creating a large system matrix. We present simulation results on standard test images under various extreme conditions and demonstrate that the quality of the image improves significantly with a small number of illumination patterns.