{"title":"单像素压缩太赫兹3D成像","authors":"Adolphe Ndagijimana;Iñigo Ederra;Miguel Heredia Conde","doi":"10.1109/TCI.2025.3564161","DOIUrl":null,"url":null,"abstract":"Terahertz (THz) imaging contends with the lack of cost-effective, off-the-shelf high-resolution array detectors and the slow acquisition speeds associated with pixel-by-pixel raster scanning. Single-pixel imaging with Compressive Sensing (CS) represents a potential solution for resolution and acquisition speed in a cost-efficient manner. Our paper introduces a novel approach for extending 2D single-pixel THz imaging systems to 3D using a single frequency. By leveraging the single-pixel approach, we achieve 3D resolution while avoiding mechanical scanning, and the use of a single frequency eliminates the need for bandwidth, a significant limitation of conventional techniques, where design of THz sources and detectors with large bandwidth remains challenging and typically complex. The Order Recursive Matching Pursuit (ORMP) algorithm is used as the sparse recovery method to exploit the sparsity/compressibility of the 3D THz signal and enable sampling at a rate far lower than that required by the Nyquist Theorem. The 2D sensing matrix is obtained by analyzing the diffracted propagation of THz imaging systems on a 2D surface perpendicular to the optical axis. Moreover, the 3D sensing matrix is based on the diffracted propagation of 2D surfaces at different sampling depth positions. Our system can quickly capture the reflective properties of every point in a 3D space using a single-pixel camera setup that leverages CS, making it a simple and efficient method for creating a fast 3D THz imaging system, particularly suited to high-frequency THz sources that operate efficiently at a single frequency or at small bandwidth.","PeriodicalId":56022,"journal":{"name":"IEEE Transactions on Computational Imaging","volume":"11 ","pages":"570-585"},"PeriodicalIF":4.2000,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10976389","citationCount":"0","resultStr":"{\"title\":\"Single-Pixel Compressive Terahertz 3D Imaging\",\"authors\":\"Adolphe Ndagijimana;Iñigo Ederra;Miguel Heredia Conde\",\"doi\":\"10.1109/TCI.2025.3564161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Terahertz (THz) imaging contends with the lack of cost-effective, off-the-shelf high-resolution array detectors and the slow acquisition speeds associated with pixel-by-pixel raster scanning. Single-pixel imaging with Compressive Sensing (CS) represents a potential solution for resolution and acquisition speed in a cost-efficient manner. Our paper introduces a novel approach for extending 2D single-pixel THz imaging systems to 3D using a single frequency. By leveraging the single-pixel approach, we achieve 3D resolution while avoiding mechanical scanning, and the use of a single frequency eliminates the need for bandwidth, a significant limitation of conventional techniques, where design of THz sources and detectors with large bandwidth remains challenging and typically complex. The Order Recursive Matching Pursuit (ORMP) algorithm is used as the sparse recovery method to exploit the sparsity/compressibility of the 3D THz signal and enable sampling at a rate far lower than that required by the Nyquist Theorem. The 2D sensing matrix is obtained by analyzing the diffracted propagation of THz imaging systems on a 2D surface perpendicular to the optical axis. Moreover, the 3D sensing matrix is based on the diffracted propagation of 2D surfaces at different sampling depth positions. Our system can quickly capture the reflective properties of every point in a 3D space using a single-pixel camera setup that leverages CS, making it a simple and efficient method for creating a fast 3D THz imaging system, particularly suited to high-frequency THz sources that operate efficiently at a single frequency or at small bandwidth.\",\"PeriodicalId\":56022,\"journal\":{\"name\":\"IEEE Transactions on Computational Imaging\",\"volume\":\"11 \",\"pages\":\"570-585\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2025-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10976389\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computational Imaging\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10976389/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Imaging","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10976389/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Terahertz (THz) imaging contends with the lack of cost-effective, off-the-shelf high-resolution array detectors and the slow acquisition speeds associated with pixel-by-pixel raster scanning. Single-pixel imaging with Compressive Sensing (CS) represents a potential solution for resolution and acquisition speed in a cost-efficient manner. Our paper introduces a novel approach for extending 2D single-pixel THz imaging systems to 3D using a single frequency. By leveraging the single-pixel approach, we achieve 3D resolution while avoiding mechanical scanning, and the use of a single frequency eliminates the need for bandwidth, a significant limitation of conventional techniques, where design of THz sources and detectors with large bandwidth remains challenging and typically complex. The Order Recursive Matching Pursuit (ORMP) algorithm is used as the sparse recovery method to exploit the sparsity/compressibility of the 3D THz signal and enable sampling at a rate far lower than that required by the Nyquist Theorem. The 2D sensing matrix is obtained by analyzing the diffracted propagation of THz imaging systems on a 2D surface perpendicular to the optical axis. Moreover, the 3D sensing matrix is based on the diffracted propagation of 2D surfaces at different sampling depth positions. Our system can quickly capture the reflective properties of every point in a 3D space using a single-pixel camera setup that leverages CS, making it a simple and efficient method for creating a fast 3D THz imaging system, particularly suited to high-frequency THz sources that operate efficiently at a single frequency or at small bandwidth.
期刊介绍:
The IEEE Transactions on Computational Imaging will publish articles where computation plays an integral role in the image formation process. Papers will cover all areas of computational imaging ranging from fundamental theoretical methods to the latest innovative computational imaging system designs. Topics of interest will include advanced algorithms and mathematical techniques, model-based data inversion, methods for image and signal recovery from sparse and incomplete data, techniques for non-traditional sensing of image data, methods for dynamic information acquisition and extraction from imaging sensors, software and hardware for efficient computation in imaging systems, and highly novel imaging system design.