Chinese Journal of Lasers, Volume. 52, Issue 11, 1110001(2025)
Image Processing-Based Method for Detecting Underwater Obstacles with Airborne Lidar
Fig. 1. Image assembled by stitching waveforms. (a) Example of lidar echo waveform stitching; (b) echo waveform containing surface water, subsurface water, and underwater obstacles; (c) echo waveform containing surface water and subsurface water
Fig. 2. Comparison of images before and after correction. (a) Example of image before correction; (b) example of corrected image
Fig. 3. Comparison of waveforms with and without water scattering removal for the obstacle located in the water scattering region
Fig. 4. Comparisons of contrast in obstacle and background areas before and after water scattering removal. (a) Contrast calculation area in image before water scattering removal; (b) contrast calculation area in image after water scattering removal; (c) contrast between obstacle and background areas before water scattering removal; (d) contrast between obstacle and background areas after water scattering removal
Fig. 5. Comparison before and after replacing local bright stripes. (a) Local image before replacing local bright stripes; (b) local image after replacing local bright stripes; (c) horizontal gradient map before replacing local bright stripes; (d) horizontal gradient map after replacing local bright stripes
Fig. 8. Experimental results of image processing. (a)(d)(g)(j) Input images; (b)(e)(h)(k) optimal scale corresponding to input images; (c)(f)(i)(l) obstacle area and connected domain labels corresponding to input images
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Hao Wang, Yan He, Deliang Lü, Chunhe Hou, Sheng Su, Pengrui Liang, Xinke Hao, Yujie Chen. Image Processing-Based Method for Detecting Underwater Obstacles with Airborne Lidar[J]. Chinese Journal of Lasers, 2025, 52(11): 1110001
Category: remote sensing and sensor
Received: Jan. 13, 2025
Accepted: Mar. 14, 2025
Published Online: Jun. 13, 2025
The Author Email: Yan He (heyan@siom.ac.cn)
CSTR:32183.14.CJL250465