{"title":"TLS的自动原位辐射校准:利用重叠扫描补偿距离和入射角效应","authors":"H. Laasch, T. Medic, N. Pfeifer, A. Wieser","doi":"10.1016/j.isprsjprs.2025.07.012","DOIUrl":null,"url":null,"abstract":"Terrestrial laser scanners (TLS) commonly record intensity of the backscattered signal as an auxiliary measurement, which can be related to material properties and used in various applications, such as point cloud segmentation. However, retrieving the material-related information from the TLS intensities is not trivial, as this information is overlayed by other systematic influences affecting the backscattered signal. One of the major factors that needs to be accounted for is the measurement configuration, which is defined by the instrument-to-target distance and angle of incidence (AOI). By obtaining measurement-configuration independent intensity (<mml:math altimg=\"si1.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>I</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">MCI</mml:mi></mml:mrow></mml:msub></mml:math>) material probing, classification, segmentation, and similar tasks can be enhanced. Current methods for obtaining such corrected intensities require additional dedicated measurement set-ups (often in a lab and with specialized targets) and manual work to estimate the effects of distance and AOI on the recorded values. Moreover, they are optimized only for specific datasets comprising a small number of targets with different material properties. This paper presents an automated method for in-situ estimation of <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>I</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">MCI</mml:mi></mml:mrow></mml:msub></mml:math>, eliminating the need for additional dedicated measurements or manual work. Instead, the proposed method uses overlapping point clouds from different scan stations of an arbitrary scene that are anyway collected during a scanning project. We demonstrate the generalizability of the proposed method across different scenes and instruments, show how the retrieved <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>I</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\"normal\">MCI</mml:mi></mml:mrow></mml:msub></mml:math> values can improve segmentation, and how they increase the comparability of the intensities between different instruments.","PeriodicalId":50269,"journal":{"name":"ISPRS Journal of Photogrammetry and Remote Sensing","volume":"97 1","pages":"648-665"},"PeriodicalIF":12.2000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automatic in-situ radiometric calibration of TLS: Compensating distance and angle of incidence effects using overlapping scans\",\"authors\":\"H. Laasch, T. Medic, N. Pfeifer, A. Wieser\",\"doi\":\"10.1016/j.isprsjprs.2025.07.012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Terrestrial laser scanners (TLS) commonly record intensity of the backscattered signal as an auxiliary measurement, which can be related to material properties and used in various applications, such as point cloud segmentation. However, retrieving the material-related information from the TLS intensities is not trivial, as this information is overlayed by other systematic influences affecting the backscattered signal. One of the major factors that needs to be accounted for is the measurement configuration, which is defined by the instrument-to-target distance and angle of incidence (AOI). By obtaining measurement-configuration independent intensity (<mml:math altimg=\\\"si1.svg\\\" display=\\\"inline\\\"><mml:msub><mml:mrow><mml:mi>I</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\\\"normal\\\">MCI</mml:mi></mml:mrow></mml:msub></mml:math>) material probing, classification, segmentation, and similar tasks can be enhanced. Current methods for obtaining such corrected intensities require additional dedicated measurement set-ups (often in a lab and with specialized targets) and manual work to estimate the effects of distance and AOI on the recorded values. Moreover, they are optimized only for specific datasets comprising a small number of targets with different material properties. This paper presents an automated method for in-situ estimation of <mml:math altimg=\\\"si1.svg\\\" display=\\\"inline\\\"><mml:msub><mml:mrow><mml:mi>I</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=\\\"normal\\\">MCI</mml:mi></mml:mrow></mml:msub></mml:math>, eliminating the need for additional dedicated measurements or manual work. Instead, the proposed method uses overlapping point clouds from different scan stations of an arbitrary scene that are anyway collected during a scanning project. 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Automatic in-situ radiometric calibration of TLS: Compensating distance and angle of incidence effects using overlapping scans
Terrestrial laser scanners (TLS) commonly record intensity of the backscattered signal as an auxiliary measurement, which can be related to material properties and used in various applications, such as point cloud segmentation. However, retrieving the material-related information from the TLS intensities is not trivial, as this information is overlayed by other systematic influences affecting the backscattered signal. One of the major factors that needs to be accounted for is the measurement configuration, which is defined by the instrument-to-target distance and angle of incidence (AOI). By obtaining measurement-configuration independent intensity (IMCI) material probing, classification, segmentation, and similar tasks can be enhanced. Current methods for obtaining such corrected intensities require additional dedicated measurement set-ups (often in a lab and with specialized targets) and manual work to estimate the effects of distance and AOI on the recorded values. Moreover, they are optimized only for specific datasets comprising a small number of targets with different material properties. This paper presents an automated method for in-situ estimation of IMCI, eliminating the need for additional dedicated measurements or manual work. Instead, the proposed method uses overlapping point clouds from different scan stations of an arbitrary scene that are anyway collected during a scanning project. We demonstrate the generalizability of the proposed method across different scenes and instruments, show how the retrieved IMCI values can improve segmentation, and how they increase the comparability of the intensities between different instruments.
期刊介绍:
The ISPRS Journal of Photogrammetry and Remote Sensing (P&RS) serves as the official journal of the International Society for Photogrammetry and Remote Sensing (ISPRS). It acts as a platform for scientists and professionals worldwide who are involved in various disciplines that utilize photogrammetry, remote sensing, spatial information systems, computer vision, and related fields. The journal aims to facilitate communication and dissemination of advancements in these disciplines, while also acting as a comprehensive source of reference and archive.
P&RS endeavors to publish high-quality, peer-reviewed research papers that are preferably original and have not been published before. These papers can cover scientific/research, technological development, or application/practical aspects. Additionally, the journal welcomes papers that are based on presentations from ISPRS meetings, as long as they are considered significant contributions to the aforementioned fields.
In particular, P&RS encourages the submission of papers that are of broad scientific interest, showcase innovative applications (especially in emerging fields), have an interdisciplinary focus, discuss topics that have received limited attention in P&RS or related journals, or explore new directions in scientific or professional realms. It is preferred that theoretical papers include practical applications, while papers focusing on systems and applications should include a theoretical background.