Dynamic Illumination and Visual Enhancement of Surface Inspection Images of Turbid Underwater Concrete Structures

Aiming at the problem of image quality degradation caused by turbid water, non-uniform illumination, and scattering effect in the surface defect detection of underwater concrete structures, firstly, the concrete surface images under different shooting distances, different sediment concentrations, and different illumination conditions were collected through laboratory experiments to simulate the concrete surface images of a reservoir dam with higher sediment concentration and deeper water depth. On this basis, an underwater image enhancement algorithm named DIVE (Dynamic Illumination and Vision Enhancement) is proposed. DIVE solves the problems of luminance unevenness and color deviation in stages through the illumination-scattering decoupling processing framework, and combines efficient computing optimization to achieve real-time processing. The lighting correction of Gaussian distributions (dynamic illumination module) was processed in stages with suspended particle scattering correction (visual enhancement module), and the bright and dark areas were balanced and color offset was corrected by local gamma correction in Lab space and dynamic decision-making of G/B channel. Through thread pool parallelization, vectorization and other technologies, the real-time requirement can be achieved at the resolution of 1920 × 1080. Tests show that DIVE significantly improves image quality in water bodies with sediment concentration up to 500 g/m<sup>3</sup>, and is suitable for complex scenes such as reservoirs, oceans, and sediment tanks.

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Publication Details

Journal
Sensors
Published
2025-09-16
DOI
https://doi.org/10.3390/s25185767
Primary Topic
Infrastructure Maintenance and Monitoring
Type
article
Field-Weighted Citation Impact
0.00

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article

Dynamic Illumination and Visual Enhancement of Surface Inspection Images of Turbid Underwater Concrete Structures

Chunhui Ma, Fei Tong, Xiaoyan Xu, Xiangyu Cao et al.
Sensors
Infrastructure Maintenance and Monitoring
article

Dynamic Illumination and Visual Enhancement of Surface Inspection Images of Turbid Underwater Concrete Structures

Chunhui Ma, Fei Tong, Xiaoyan Xu, Xiangyu Cao, Jie Yang, Gao Mingzhe, Lin Cheng
article en

Abstract

Aiming at the problem of image quality degradation caused by turbid water, non-uniform illumination, and scattering effect in the surface defect detection of underwater concrete structures, firstly, the concrete surface images under different shooting distances, different sediment concentrations, and different illumination conditions were collected through laboratory experiments to simulate the concrete surface images of a reservoir dam with higher sediment concentration and deeper water depth. On this basis, an underwater image enhancement algorithm named DIVE (Dynamic Illumination and Vision Enhancement) is proposed. DIVE solves the problems of luminance unevenness and color deviation in stages through the illumination-scattering decoupling processing framework, and combines efficient computing optimization to achieve real-time processing. The lighting correction of Gaussian distributions (dynamic illumination module) was processed in stages with suspended particle scattering correction (visual enhancement module), and the bright and dark areas were balanced and color offset was corrected by local gamma correction in Lab space and dynamic decision-making of G/B channel. Through thread pool parallelization, vectorization and other technologies, the real-time requirement can be achieved at the resolution of 1920 × 1080. Tests show that DIVE significantly improves image quality in water bodies with sediment concentration up to 500 g/m<sup>3</sup>, and is suitable for complex scenes such as reservoirs, oceans, and sediment tanks.

SensorsVol. 25(18)
Xi'an University of Architecture and Technology (CN), Nanjing Hydraulic Research Institute (CN), Xi'an University of Technology (CN)
National Natural Science Foundation of China, Education Department of Shaanxi Province
Openalex Percentile: Top 74%
Infrastructure Maintenance and Monitoring
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