Infrared and Laser Engineering, Volume. 52, Issue 6, 20230169(2023)

Recent progress and prospect of laser imaging processing technology (invited)

Yihua Hu1,2,3,4 and Luda Zhao1,2,3,4、*
Author Affiliations
  • 1College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China
  • 2State Key Laboratory of Pulsed Power Laser Technology, National University of Defense Technology, Hefei 230037, China
  • 3Anhui Province Key Laboratory of Electronic Restriction, National University of Defense Technology, Hefei 230037, China
  • 4Information Security Research Center, Hefei Comprehensive National Science Center, Hefei 230037, China
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    References(109)

    [1] [1] Hu Y H. Laser Imaging Target Reconnaissance[M]. Beijing: National Defense Industry Press, 2014: 1.(in Chinese)

    [3] [3] Hu Y H. Applied They Method of Laser Coherent Detection [M]. Beijing: Science Press, 2022. (in Chinese)

    [8] [8] Pathak R S. The Wavelet Transfm[M]. Paris: Atlantis Press, 2009.

    [29] [29] Rakotosaona M J, La Barbera V, Guerrero P, et al. Pointclean: Learning to denoise remove outliers from dense point clouds[C]Computer Graphics Fum. 2020, 39(1): 185203.

    [30] [30] Guerrero P, Kleiman Y, Ovsjanikov M, et al. Pcp learning local shape properties from raw point clouds[C]Computer Graphics Fum, 2018, 37(2): 7585.

    [42] J Su, M P Mccormick, Z Liu, et al. Obtaining a ground-based lidar geometric form factor using coincident spacebornelidar measurements. Applied Optics, 49, 108-113(2010).

    [43] [43] Zhang X, Xue Z. Geometrical err crection research in high precision 2D laser measuring instrument[C]Sixth International Symposium on Precision Engineering Measurements Instrumentation, SPIE, 2010, 7544: 17101717.

    [44] [44] Liu Y, Chen S, Zhang Y, et al. Algithm of geometry crection f airbne 3D scanning laser radar[C]2009 International Conference on Optical Instruments Technology: Advanced Sens Technologies Applications. SPIE, 2009, 7508: 452462.

    [46] [46] Rewehel E M, Li J, Keshk H M, et al. Geometric crection of aerial camera LiDAR hybrid system data using GNSSIMU[C]2022 IEEE 13th International Conference on Software Engineering Service Science (ICSESS), IEEE, 2022: 5458.

    [47] [47] Chen B, Pang Y. A denoising approach f detection of canopy ground from ICESat2''s airbne simulat data in Maryl, USA[C]AOPC 2015: Advances in Laser Technology Applications, SPIE, 2015, 9671: 383387.

    [49] Y Li, H Fu, J Zhu, et al. A filtering method for ICESat-2 photon point cloud data based on relative neighboring relationship and local weighted distance statistics. IEEE Geoscience and Remote Sensing Letters, 18, 1891-1895(2020).

    [51] X Zhu, S Nie, C Wang, et al. A noise removal algorithm based on OPTICS for photon-counting LiDAR data. IEEE Geoscience and Remote Sensing Letters, 18, 1471-1475(2020).

    [52] [52] Zaman F, Wong Y P, Ng B Y. Densitybased denoising of point cloud[C]9th International Conference on Robotic, Vision, Signal Processing Power Applications: Empowering Research Innovation. Springer Singape, 2017: 287295.

    [54] [54] Qi C R, Su H, Mo K, et al. Point: Deep learning on point sets f 3D classification segmentation[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2017: 652660.

    [55] [55] Roveri R, Öztireli A C, Pele I, et al. Pointpros: Consolidation of point clouds with convolutional neural wks[C]Computer Graphics Fum, 2018, 37(2): 8799.

    [56] [56] Himmelsbach M, Hundelshausen F V, Wuensche H J. Fast segmentation of 3D point clouds f ground vehicles[C]2010 IEEE Intelligent Vehicles Symposium. IEEE, 2010: 560565.

    [57] [57] Zermas D, Izzat I, Papanikolopoulos N. Fast segmentation of 3D point clouds: A paradigm on lidar data f autonomous vehicle applications[C]2017 IEEE International Conference on Robotics Automation (ICRA). IEEE, 2017: 50675073.

    [58] [58] Moosmann F, Pink O, Stiller C. Segmentation of 3D lidar data in nonflat urban environments using a local convexity criterion[C]2009 IEEE Intelligent Vehicles Symposium, 2009: 215220.

    [60] [60] Narksri P, Takeuchi E, Ninomiya Y, et al. A sloperobust caded ground segmentation in 3D point cloud f autonomous vehicles[C]2018 21st International Conference on Intelligent Transptation Systems (ITSC), IEEE, 2018: 497504.

    [61] [61] Paigwar A, Erkent , SierraGonzalez D, et al. Gnd: Fast ground plane estimation point cloud segmentation f autonomous vehicles[C]2020 IEEERSJ International Conference on Intelligent Robots Systems (IROS), 2020: 21502156.

    [62] [62] Xu J, Zhang R, Dou J, et al. Rpv: A deep efficient rangepointvoxel fusion wk f lidar point cloud segmentation[C]Proceedings of the IEEECVF International Conference on Computer Vision, 2021: 1602416033.

    [73] [73] Yang J, Li H, Jia Y. Goicp: Solving 3D registration efficiently globally optimally[C]Proceedings of the IEEE International Conference on Computer Vision, 2013: 14571464.

    [74] [74] Rosen D M, Carlone L, Beira A S, et al. A certifiably crect algithm f synchronization over the special Euclidean group[C]Algithmic Foundations of Robotics XII: Proceedings of the Twelfth Wkshop on the Algithmic Foundations of Robotics. Cham: Springer International Publishing, 2020: 6479.

    [75] [75] Izatt G, Dai H, Tedrake R. Globally optimal object pose estimation in point clouds with mixedinteger programming[C]Robotics Research: The 18th International Symposium ISRR. Springer International Publishing, 2020: 695710.

    [76] [76] Maturana D, Scherer S. Vox: A 3D convolutional neural wk f realtime object recognition[C]2015 IEEERSJ International Conference on Intelligent Robots Systems (IROS), IEEE, 2015: 922928.

    [77] [77] Wu Z, Song S, Khosla A, et al. 3D Shapes: A deep representation f volumetric shapes[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2015: 19121920.

    [78] [78] Aoki Y, Gofth H, Srivatsan R A, et al. Pointlk: Robust & efficient point cloud registration using point[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2019: 71637172.

    [79] [79] Chu J, Nie C. Multiview point clouds registration stitching based on SIFT feature[C]2011 3rd International Conference on Computer Research Development, IEEE, 2011, 1: 274278.

    [81] [81] Zhong Y, Bai F, Liu Y, et al. Point cloud splicing based on 3DHarris operat[C]2021 3rd International Symposium on Smart Healthy Cities (ISHC), IEEE, 2021: 6166.

    [84] [84] Hu Y. They Technology of Laser Imaging Based Target Detection[M]. Singape: Springer Press, 2018.

    [85] [85] Moosmann F, Fraid T. Motion estimation from range images in dynamic outdo scenes[C]2010 IEEE International Conference on Robotics Automation, IEEE, 2010: 142147.

    [86] [86] Dewan A, Caselitz T, Tipaldi G D, et al. Motionbased detection tracking in 3d lidar scans[C]2016 IEEE International Conference on Robotics Automation (ICRA), IEEE, 2016: 45084513.

    [87] [87] Dewan A, Caselitz T, Tipaldi G D, et al. Rigid scene flow f 3D lidar scans[C]2016 IEEERSJ International Conference on Intelligent Robots Systems (IROS), IEEE, 2016: 17651770.

    [88] [88] Qi C R, Yi L, Su H, et al. Point++: Deep hierarchical feature learning on point sets in a metric space[C]Advances in Neural Infmation Processing Systems, 2017: 30.

    [90] [90] Zhou Y, Tuzel O. Voxel: Endtoend learning f point cloud based 3D object detection[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition. 2018: 44904499.

    [91] [91] Liu X, Qi C R, Guibas L J. Flow3d: Learning scene flow in 3d point clouds[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2019: 529537.

    [92] [92] Wang Z, Li S, HowardJenkins H, et al. Flow3d++: Geometric losses f deep scene flow estimation[C]Proceedings of the IEEECVF Winter Conference on Applications of Computer Vision, 2020: 9198.

    [93] [93] Mayer N, Ilg E, Hausser P, et al. A large dataset to train convolutional wks f disparity, optical flow, scene flow estimation[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2016: 40404048.

    [94] [94] Gojcic Z, Litany O, Wieser A, et al. Weakly supervised learning of rigid 3D scene flow[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2021: 56925703.

    [96] [96] Tishchenko I, Lombardi S, Oswald M R, et al. Selfsupervised learning of nonrigid residual flow egomotion[C]2020 International Conference on 3D Vision (3DV), IEEE, 2020: 150159.

    [97] [97] Baur S A, Emmerichs D J, Moosmann F, et al. SLIM: Selfsupervised LiDAR scene flow motion segmentation[C]Proceedings of the IEEECVF International Conference on Computer Vision, 2021: 1312613136.

    [98] [98] Behl A, Phalidou D, Donné S, et al. Pointflow: Learning representations f rigid motion estimation from point clouds[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2019: 79627971.

    [99] [99] Milioto A, Vizzo I, Behley J, et al. Range++: Fast accurate lidar semantic segmentation[C]2019 IEEERSJ International Conference on Intelligent Robots Systems (IROS), IEEE, 2019: 42134220.

    [100] [100] Ctinhal T, Tzelepis G, Erdal Aksoy E. SalsaNext: Fast, uncertaintyaware semantic segmentation of LiDAR point clouds[C]International Symposium on Visual Computing. Cham: Springer, 2020: 207222.

    [105] [105] Sun J, Dai Y, Zhang X, et al. Efficient spatialtempal infmation fusion f Lidarbased 3d moving object segmentation[C]2022 IEEERSJ International Conference on Intelligent Robots Systems (IROS), IEEE, 2022: 1145611463.

    [108] Y Chen, J Tang, C Jiang, et al. The accuracy comparison of three simultaneous localization and mapping (SLAM)-based indoor mapping technologies. Sensors, 10, 3225(2018).

    [109] [109] Yin T, Zhou X, Krähenbühl P. Multimodal virtual point 3D detection[C]Advances in Neural Infmation Processing Systems, 2021, 34: 1649416507.

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    Yihua Hu, Luda Zhao. Recent progress and prospect of laser imaging processing technology (invited)[J]. Infrared and Laser Engineering, 2023, 52(6): 20230169

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    Paper Information

    Category: Invited paper

    Received: Mar. 27, 2023

    Accepted: --

    Published Online: Jul. 26, 2023

    The Author Email: Zhao Luda (zhaoluda@nudt.edu.cn)

    DOI:10.3788/IRLA20230169

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