[1]GUAN Fengxu,WU Zhuofeng,ZHANG Yuzhu,et al.High-precision and fast three-dimensional reconstruction of underwater images driven by the shape-from-shading algorithm[J].CAAI Transactions on Intelligent Systems,2025,20(3):670-678.[doi:10.11992/tis.202401017]
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High-precision and fast three-dimensional reconstruction of underwater images driven by the shape-from-shading algorithm

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 20 Number of periods: 2025 3 Page number: 670-678 Column: 学术论文—智能系统 Public date: 2025-05-05
Title:
High-precision and fast three-dimensional reconstruction of underwater images driven by the shape-from-shading algorithm
Author(s):
GUAN Fengxu1; 2;  WU Zhuofeng2;  ZHANG Yuzhu1;  TANG Shiwen1;  YAO Jiahao1;  DU Xue1
1. College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China;
2. Nanhai Institute, Harbin Engineering University, Sanya 572024, China
Keywords:
side-scan sonar image; shape from shading; 3D reconstruction; linearization method; seabed detection; high-precision imaging; underwater image; image processing
CLC:
TP18
DOI:
10.11992/tis.202401017
Abstract:
Shape from shading (SFS) represents an indispensable key technique in three-dimensional (3D) reconstruction. It leverages the luminance information of the gray scale of the object in a single image to determine the relative height and the surface normal vector of each point, and the existing linearization algorithms of SFS leverage a Taylor series approach for the expansion, thereby ignoring the influence of the higher-order part, which causes issues, such as the inaccuracy of the reconstructed image in 3D. Thus, to solve the accuracy problem of 3D reconstruction, a high-precision, fast 3D reconstruction method for underwater images is proposed based on the enhancement driven by the SFS algorithm. This method solves the existing issues regarding insufficient data utilization and low iteration speed, thereby improving the accuracy of 3D reconstruction. Regarding the application to real and virtual images for the experimental evaluation and quantitative analysis of 3D reconstruction, the proposed SFS algorithm-enhanced high-precision and fast 3D reconstruction method for underwater images delivers satisfactory signal-to-noise ratios and entropy values regarding image information compared with classical SFS-linearization and SFS-minimization algorithms.
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