Advanced Search
WEI Shuo, ZHAO Nanxiang, LI Minle, HU Yihua. Single photon denoising algorithm combined with improved DBSCAN and statistical filtering[J]. LASER TECHNOLOGY, 2021, 45(5): 601-606. DOI: 10.7510/jgjs.issn.1001-3806.2021.05.011
Citation: WEI Shuo, ZHAO Nanxiang, LI Minle, HU Yihua. Single photon denoising algorithm combined with improved DBSCAN and statistical filtering[J]. LASER TECHNOLOGY, 2021, 45(5): 601-606. DOI: 10.7510/jgjs.issn.1001-3806.2021.05.011
shu

Single photon denoising algorithm combined with improved DBSCAN and statistical filtering

  • 1.

    State Key Laboratory of Pulsed Power Laser Technology, School of Electronic Warfare, National Defense University, Hefei 230037, China

  • 2.

    Advanced Laser Technology Laboratory of Anhui Province, School of Electronic Warfare, National Defense University, Hefei 230037, China

More Information
  • Received Date: September 28, 2020
  • Revised Date: December 06, 2020
  • Published Date: September 24, 2021
    Graphical Abstract
    • Abstract
  • In order to solve the problem of excessive noise point clouds in the photon counting lidar detection data, a single photon point cloud denoising method based on a combination of improved density-based spatial clustering of applications with noise (DBSCAN) algorithm and statistical filtering algorithm was adopted. The actual flight data of multiple altimeter beam experimental lidar provided by National Aeronautics and Space Administration was experimental data. First, the point cloud density was obtained through the k-dimensional tree for rough denoising, and then the improved DBSCAN algorithm and statistical filtering algorithm were used for fine denoising. The theoretical analysis and experimental verification has achieved good results. The results show that the target point cloud recognition rate in the experimental area is above 85%, and the performance is better than the classic radius filtering algorithm. This result is helpful for photon data denoising.
    • FullText(HTML)
    • References (21)
  • [1]
    XU Q, XIE X M, ZHANG W, et al. The progress of semiconductor quantum dot based quantum emitter [J]. Laser Technology, 2020, 44(5): 575-586(in Chinese).
    [2]
    TANG X M, LI G Y. Development and prospect of laser altimetry satellite [J]. International Space, 2017(11): 13-18(in Chinese).
    [3]
    LUO H J, ZHOU R L, ZHANG Y T. Theoretical analysis of detection performance and range accuracy of photon ladar[J]. Laser Technology, 2014, 38(3): 411-416(in Chinese). http://en.cnki.com.cn/Article_en/CJFDTOTAL-JGJS201403028.htm
    [4]
    SHU R, HUANG G H, HOU L B, et al. Multi-channel photon counting three-dimensional imaging laser radar system using fiber array coupled Geiger-mode avalanche photodiode[J]. Proceedings of the SPIE, 2012, 8542: 1-10. DOI: 10.1117/12.974365
    [5]
    FANG J, SHE Ch, LIU J P. A denoising method based on photon counting lidar[J]. Ship Electronic Warfare, 2019, 42(4): 10-15(in Chinese).
    [6]
    OH M S, KONG H J, KIM T H, et al. Multihit mode direct-detection laser radar system using a Geiger-mode avalanche photodiode[J]. Review of Scientific Instruments, 2010, 81(3): 1-7. http://europepmc.org/abstract/MED/20370163
    [7]
    FOUCHE D G. Detection and false-alarm probabilities for laser radars that use Geiger-mode detectors[J]. Applied Optics, 2003, 42(27): 5388-5398. DOI: 10.1364/AO.42.005388
    [8]
    MILSTEIN A B, JIANG L A, LUU J X. Acquisition algorithm for direct-detection ladars with Geiger-mode avalanche photodiodes[J]. Applied Optics, 2008, 47(2): 296-311. DOI: 10.1364/AO.47.000296
    [9]
    HORAN K H, KEREKES J P. An automated statistical analysis approach to noise reduction for photon-counting lidar systems [C]//IEEE International Geoscience and Remote Sensing Symposium. NewYork, USA: IEEE, 2013: 4336-4339.
    [10]
    HERZFELD U C, MCDONALD B W, WALLIN B F, et al. Algorithm for detection of ground and canopy cover in micropulse photon-counting lidar altimeter data in preparation for the ICESat-2 mission [J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(4) : 2109-2125. DOI: 10.1109/TGRS.2013.2258350
    [11]
    LI K, ZHANG Y Sh, TONG X Ch, et al. Research on de-noising and filtering algorithm of single photon lidar data[J]. Navigation and Control, 2020, 19(1): 67-76(in Chinese).
    [12]
    LI M, GUO Y, YANG G, et al. A push-broom photon counting lidar point cloud filtering algorithm and its verification[J]. Science Technology and Engineering, 2017, 17(9): 53-58 (in Chinese).
    [13]
    XU Y T, LI G Y, QIU Ch X, et al. Single-photon laser data processing technology based on terrain correlation and least square curve fitting[J]. Infrared and Laser Engineering, 2019, 48(12): 148-157(in Chinese). http://en.cnki.com.cn/Article_en/CJFDTotal-HWYJ201912019.htm
    [14]
    MCGILL M, MARKUS T, SCOTT V S, et al. The multiple altimeter beam experimental lidar (MABEL): An airborne simulator for the ICESat-2 mission[J]. Journal of Atmospheric and Oceanic Technology, 2013, 30(2): 345-352. DOI: 10.1175/JTECH-D-12-00076.1
    [15]
    BRUNT K M, NEUMANN T A, AMUNDSON J M, et al. MABEL photon-counting laser altimetry data in Alaska for ICESat-2 simulations and development[J]. Cryosphere, 2016, 10(4): 1707-1719. DOI: 10.5194/tc-10-1707-2016
    [16]
    YU F L. Research on ladar 3-D point cloud data processing methods based on single photon detection [D]. Harbin: Harbin University of Technology, 2016: 57-63(in Chinese).
    [17]
    ZHOU H, LI S, WANG L X, et al. Influence of noise on range error for satellite laser altimeter [J]. Infrared and Laser Engineering, 2015, 449(8): 2256 - 2261(in Chinese). http://www.zhangqiaokeyan.com/academic-journal-cn_infrared-laser-engineering_thesis/0201236126080.html
    [18]
    LIU Y, SUN Sh Y. Laser point cloud denoising based on principal component analysis and surface fitting[J]. Laser Technology, 2020, 44(4): 497-502(in Chinese).
    [19]
    WANG T, SHEN Y H, YAO J Q. Research on laser radar echo signal denoising based on wavelet threshold method[J]. Laser Technology, 2019, 43(1): 63-68(in Chinese). http://en.cnki.com.cn/Article_en/CJFDTotal-JGJS201901013.htm
    [20]
    LIU Zh P, YU Q Y, CHA J F. Rapid transformation from spatial rectangular coordinates to two common coordinates[J]. Science of Surveying and Mapping, 2015, 40(3): 8-11(in Chinese).
    [21]
    SANG J. Non-iteration method for inversion of space geodetic rectangular coordinates and geodetic coordinates[J]. Bulletin of Surveying and Mapping, 2000(5): 37-39(in Chinese).
    • Related Articles

Catalog

    Get Citation
    PDF
    XML
    Article views (14) PDF downloads (19) Cited by()
    Turn off MathJax
    Article Contents
    Abstract
    References

    Links：

    more+

    Website Copyright © Editorial Department of LASER TECHNOLOGY 蜀ICP备10038222号-1

    Address：No. 7, Section 4, Renmin South Road, Chengdu, Sichuan Province, China Post Code：610041

    Tel：028-68011091/68011046 Email: jgjs@vip.163.com

    Supported by: Beijing Renhe Information Technology Co., Ltd. 

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return