传统激光雷达在透雾成像过程中受探测接收灵敏度限制无法提取淹没在强后向散射噪声内的目标信号,难以达到透雾效果。本文提出单量估计法的面阵盖革模式雪崩光电二极管激光雷达透雾成像算法,依据盖革模式触发探测模型,通过对回波光子进行极大似然估计得到后向散射分布,提取目标回波位置,抑制了后向散射噪声,达到透雾成像的目的。搭建了室内激光透雾成像实验平台,获取了不同浓度下的透雾成像数据。实验结果表明,与峰值法和双量估计法相比,单量估计法能最大程度恢复目标像素数,衰减系数为0.11 m
Conventional lidar cannot be used to extract a target signal from the strong backscatter noise in fog-penetration imaging because of the inherent detection and reception sensitivity limitations of lidar. Therefore, achieving the fog penetration effect is difficult. To address this problem, a novel single-quantile estimation method was proposed for the fog-penetration imaging algorithm based on Geiger-mode avalanche-photodiode lidar. According to the Geiger-mode trigger detection model, the backscattering distribution was obtained through the maximum likelihood estimation of the echo photon. Fog-penetration imaging was then achieved through subsequent extraction of the target echo position and backscattering noise suppression. The experimental platform of laser fog-penetration imaging was developed, and fog-penetration imaging under various fog conditions were performed. The results revealed that the single-estimation method outperformed the peak and double-estimation methods. When the attenuation coefficient was 0.11 m
-1
, the distance information recovery of the peak method increased by 8.26% and the target recovery degree decreased by 16.22%. When the attenuation coefficient was 0.86 m
-1
, the distance information recovery of the peak method increased by 86.86%, and the target recovery degree increased by 20.51%. When the attenuation coefficient was 2.37 m
-1
, the distance information recovery of the peak method increased by 253.19%, and the target recovery degree increased by 53.44%. A high degree of target restoration was achieved in signal-level dehazing by using the single-quantity estimation method.
SHU H L . Study on Natural Image Dehazing Algorithm and Objective Evaluation of Blur [D]. Nanjing : Nanjing University of Posts and Telecommunications , 2020 . (in Chinese)
ZHU Q , MAI J , SHAO L . A fast single image haze removal algorithm using color attenuation prior [J]. IEEE Transactions on Image Processing , 2015 , 24 ( 11 ): 3522 - 3533 .
钱雯 . 基于深度学习的图像去雾算法研究 [D]. 南京 : 南京邮电大学 , 2020 .
QIAN W . Research on Image Fog Removal Algorithm Based on Deep Learning [D]. Nanjing : Nanjing University of Posts and Telecommunications , 2020 . (in Chinese)
LI Y F , REN J B , HUANG Y F . Remote sensing image fog removal algorithm based on deep learning [J/OL]. Computer Application Research : 1 - 8 [ 2021-03-29 ]. https://doi.org/10.19734/j.issn.1001-3695.2020.07.0270. https://doi.org/10.19734/j.issn.1001-3695.2020.07.0270. (in Chinese)
LUO H J , YUAN X H , ZHOU R L . Research on detection performance and false alarm suppression of GM-APD lidar [J]. Laser & Infrared , 2014 , 44 ( 2 ): 175 - 179 . (in Chinese)
WANG S . Research on Improving Image Quality of Laser Active Imaging System in Fog [D]. Harbin : Harbin Institute of Technology , 2012 . (in Chinese)
THANH L T , THANH D N H , HUE N M , et al . Single Image dehazing based on adaptive histogram equalization and linearization of gamma correction [C]. 2019 25th Asia-Pacific Conference on Communications , 2019 : 36 - 40 .
BONNIER D , LELIEVRE S , DEMERS L . On the safe use of long-range laser active imager in the near-infrared for homeland security [J]. SPIE , 2006 , 6206 : 62060 A-1-9.
WANG J G , LI Y Q . An improved image defogging algorithm based on Retinex theory [J]. Computer Knowledge and Technology , 2019 , 15 ( 26 ): 200 - 201,203 . (in Chinese)
SATAT G , TANCIK M , RASKAR R . Towards photography through realistic fog [J]. 2018 IEEE International Conference on Computational Photography (ICCP) , Pittsburgh , PA, 2018 : 1 - 10 .
高国强 . 雨雾天环境中对激光传输衰减的研究 [D]. 西安 : 西安科技大学 , 2014 .
GAO G Q . Research on Attenuation of Laser Transmission in Rain and Fog [D]. Xi'an : Master's Thesis of Xi 'an University of Science and Technology , 2014 . (in Chinese)
MA L , LU W , JIANG P , et al .. Research on 3d reconstruction algorithm of gm-apd lidar based on matched filtering [J]. Infrared and Laser Engineering , 2020 , 49 ( 2 ): 153 - 160 . (in Chinese)