Filtering vegetation from terrestrial point clouds with low-cost near infrared cameras

被引:14
|
作者
Alba, Mario [1 ]
Luigi, Barazzetti [1 ]
Roncoroni, Fabio [1 ]
Scaioni, Marco [1 ]
机构
[1] Dept BEST, I-20133 Milan, Italy
关键词
terrestrial laser scanning; filtering vegetation; NIR camera; point clouds; NDVI filter; CLOSE-RANGE PHOTOGRAMMETRY; LASER SCANNER; ROCKFALL; CALIBRATION; SPAIN;
D O I
10.5721/ItJRS20114325
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
In applications relating to the reconstruction of a rock face's surface by Terrestrial Laser Scanning (TLS), the overgrown vegetation does not allow one to correctly accomplish this task. In standard Airborne Laser Scanning surveys, the vegetation is filtered out by using spatial filters that exploit the availability of multiple echoes. The same approach does not work efficiently in the case of a rock face. This is due to the morphological complexity, that is typical of such surfaces. For this reason a new system for the automatic recognition of vegetation using a NI R camera was designed and implemented. It is based on a set of images acquired with a low-cost SLR digital camera modified to capture also the NIR component. Such camera is integrated and calibrated with respect to the TLS sensor. A vegetation filter based on the analysis of the NIR component allows one to locate vegetated areas, that can be automatically removed from the data set. In the paper we would like to give an introduction to the procedure used for camera setup, calibration, and the filtering algorithms implemented.
引用
收藏
页码:55 / 75
页数:21
相关论文
共 50 条
  • [31] Comparing Filtering Techniques for Removing Vegetation from UAV-Based Photogrammetric Point Clouds
    Anders, Niels
    Valente, Joao
    Masselink, Rens
    Keesstra, Saskia
    DRONES, 2019, 3 (03) : 1 - 14
  • [32] Low-cost near-infrared measurement of subcutaneous fat for newborn malnutrition
    McEwan, A. L.
    Bian, S.
    Gargiulo, G. D.
    Morhard, R.
    Jones, P.
    Mustafa, F. H.
    Bek, B. Emily
    Jeffery, H. E.
    NANOSENSORS, BIOSENSORS, AND INFO-TECH SENSORS AND SYSTEMS 2014, 2014, 9060
  • [33] Low-cost, high-speed near infrared reflectance confocal microscope
    Gong, Cheng
    Kulkarni, Nachiket
    Zhu, Wenbin
    Nguyen, Christopher David
    Curiel-Lewandrowski, Clara
    Kang, Dongkyun
    BIOMEDICAL OPTICS EXPRESS, 2019, 10 (07) : 3497 - 3505
  • [34] A low-cost near-infrared digital camera for fire detection and monitoring
    Burnett, Jonathan D.
    Wing, Michael G.
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2018, 39 (03) : 741 - 753
  • [35] Reflow soldering for low-cost electronics using near-infrared LEDs
    Wenger, Thomas
    Schletterer, Philipp
    Reichenberger, Marcus
    FLEXIBLE AND PRINTED ELECTRONICS, 2025, 10 (01):
  • [36] A Low-cost Fiber-based Near-Infrared Heterodyne Interferometer
    Pallanca, Laurent
    Vio, Cristobal
    Michael, Ernest A.
    OPTICAL AND INFRARED INTERFEROMETRY III, 2012, 8445
  • [37] A Simple and Low-Cost Apparatus of Near-Infrared for Defect Examination in Tomato
    Nisa, Wandiyatun
    Mudeng, Vicky
    Ernawati, Lusi
    Tarigan, Regina Ayunita
    2020 10TH ELECTRICAL POWER, ELECTRONICS, COMMUNICATIONS, CONTROLS AND INFORMATICS SEMINAR (EECCIS), 2020, : 147 - 150
  • [38] COMPACT LOW-COST INFRARED SPECTROPHOTOMETER
    MULLER, RH
    ANALYTICAL CHEMISTRY, 1966, 38 (06) : A121 - &
  • [39] CONSTRUCTION OF A LOW-COST INFRARED VIEWER
    YEE, JL
    MOBUS, BC
    JOURNAL OF THE FORENSIC SCIENCE SOCIETY, 1969, 9 (1-2): : 80 - &
  • [40] Approaches to low-cost infrared sensing
    Reyner, Charles J.
    Ariyawansa, Gamini
    Claflin, Bruce
    Duran, Joshua M.
    Grzybowski, Gordon J.
    APPLIED OPTICS, 2021, 60 (25) : G162 - G169