Small Target Radiometric Performance of Drone-Based Hyperspectral Imaging Systems

被引:1
|
作者
Conran, David N. [1 ]
Ientilucci, Emmett J. [1 ]
Bauch, Timothy D. [1 ]
Raqueno, Nina G. [1 ]
机构
[1] Rochester Inst Technol, Chester F Carlson Ctr Imaging Sci, Digital Imaging & Remote Sensing Lab, 54 Lomb Mem Dr, Rochester, NY 14623 USA
关键词
small target radiometry; radiometric performance; point targets; hyperspectral; imaging; small unmanned aircraft systems; UAS; UAV; convex mirrors;
D O I
10.3390/rs16111919
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Hyperspectral imaging systems frequently rely on spectral rather than spatial resolving power for identifying objects within a scene. A hyperspectral imaging system's response to point targets under flight conditions provides a novel technique for extracting system-level radiometric performance that is comparable to spatially unresolved objects.The system-level analysis not only provides a method for verifying radiometric calibration during flight but also allows for the exploration of the impacts on small target radiometry, post orthorectification. Standard Lambertian panels do not provide similar insight due to the insensitivity of orthorectification over a uniform area. In this paper, we utilize a fixed mounted hyperspectral imaging system (radiometrically calibrated) to assess eight individual point targets over 18 drone flight overpasses. Of the 144 total observations, only 18.1% or 26 instances are estimated to be within the uncertainty of the predicted entrance aperture-reaching radiance signal. For completeness, the repeatability of Lambertian and point targets are compared over the 18 overpasses, where the effects of orthorectification drastically impact the radiometric estimate of point targets. The unique characteristic that point targets offer, being both a known spatial and radiometric source, is that they are the only field-deployable method for understanding the small target radiometric performance of drone-based hyperspectral imaging systems.
引用
收藏
页数:24
相关论文
共 50 条
  • [31] Stochastic Modeling for Assessing the Reliability and Availability of Drone-Based Surveillance Systems
    Lins, Luan
    Nascimento, Erick
    Dantas, Jamilson
    Araujo, Jean
    Maciel, Paulo
    18TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE, SYSCON 2024, 2024,
  • [32] Selection on Optimal Bands to Estimate Yield of the Chinese Cabbage Using Drone-based Hyperspectral Image
    Na, Sang-il
    Park, Chan-won
    So, Kyu-ho
    Ahn, Ho-yong
    Lee, Kyung-do
    KOREAN JOURNAL OF REMOTE SENSING, 2019, 35 (03) : 375 - 387
  • [33] Towards a Holistic Performance Evaluation Framework for Drone-Based Object Detection
    Petrides, P.
    Kyrkou, C.
    Kolios, P.
    Theocharides, T.
    Panayiotou, C.
    2017 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS'17), 2017, : 1785 - 1793
  • [34] Detection Thresholds for Vertical Gains in VR and Drone-based Telepresence Systems
    Matsumoto, Keigo
    Langbehn, Eike
    Narumi, Takuji
    Steinicke, Frank
    2020 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES (VR 2020), 2020, : 101 - 107
  • [35] Drone-based Risk Management of Autonomous Systems Using Contracts and Blockchain
    Ul Muram, Faiz
    Javed, Muhammad Atif
    2021 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION AND REENGINEERING (SANER 2021), 2021, : 679 - 688
  • [36] Drone-based polarization imaging for phenotyping peanut in response to leaf spot disease
    Larsen, Joshua C.
    Austin, Robert
    Dunne, Jeffrey
    Kudenov, Michael W.
    POLARIZATION: MEASUREMENT, ANALYSIS, AND REMOTE SENSING XV, 2022, 12112
  • [37] Fertilizer Effects on Hemp Biomass Production Detected By Drone-Based Spectral Imaging
    Brym, Zachary
    Monserratel, Luis A.
    Her, Young Gu
    Stanford, Jill
    HORTSCIENCE, 2021, 56 (09) : S21 - S22
  • [38] Evaluating H2 Infiltration via Drone-Based Thermal Imaging
    Imponenti, Luca
    Boyle, Keith
    Shininger, Ryan
    Wendelin, Tim
    Price, Hank
    SOLARPACES 2022, 28TH INTERNATIONAL CONFERENCE ON CONCENTRATING SOLAR POWER AND CHEMICAL ENERGY SYSTEMS, VOL 1, 2023,
  • [39] Spectral variability in fine-scale drone-based imaging spectroscopy does not impede detection of target invasive plant species
    Huelsman, Kelsey
    Epstein, Howard
    Yang, Xi
    Mullori, Lydia
    Cervena, Lucie
    Walker, Roderick
    FRONTIERS IN REMOTE SENSING, 2023, 3
  • [40] Performance Analysis And Radiometric Correction of Novel Molecular Hyperspectral Imaging System
    Liu Hong-ying
    Li Qing-li
    Gu Bin
    Wang Yi-ting
    Xue Yong-qi
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32 (11) : 3161 - 3166