数字海洋与水下攻防2025，Vol.8Issue(5)：529-536,8.DOI:10.19838/j.issn.2096-5753.2025.05.002
基于成像双曲线修正模型的水下图像增强
Underwater Image Enhancement Based on Hyperbolic Imaging Correction Model
摘要
Abstract
Underwater optical images are the most direct and efficient way to obtain underwater information,but they often suffer from severe color distortion and contrast degradation due to light absorption and scattering.Prevailing deep learning methods require extensive paired data and have limitations such as complex network architectures and high computational costs.In this paper,a hyperbolic imaging correction model for underwater image enhancement based on zero-reference learning framework is proposed.It transforms image enhancement problem into a specific parametric graph estimation task.In the color enhancement stage,a physically grounded color correction model derived from haze imaging principle is developed.A lightweight network is designed to estimate dynamic adjustment parameters and to eliminate dispersion and color cast,while optimizing pixel-level dynamic range.In the luminance optimization stage,a non-linear luminance mapping function coupled with an adaptive brightness correction model is deployed,which is inspired by the human visual system.Thus,residual dynamic range compression and illumination constraints from prior processing are rectified,global luminance is calibrated and model bias is corrected.The core contribution of this model lies in the zero-reference learning feature,and the framework operates without paired underwater data.Experiments on benchmark datasets show that the proposed method is competitive in both subjective and quantitative metrics,validating the methodological efficacy and practical viability of this physics-inspired correction framework for underwater vision.关键词
水下图像/图像增强/零参考/成像模型Key words
underwater image/image enhancement/zero-reference/imaging model分类
信息技术与安全科学引用本文复制引用
HUANG Yifan,LIU Yachen,CHEN Zhe,CHEN Feng..基于成像双曲线修正模型的水下图像增强[J].数字海洋与水下攻防,2025,8(5):529-536,8.基金项目
广西杰出青年科学基金项目"水下小孔径超增益高阶矢量声呐应用基础研究"(2025GXNSFFA069010) （2025GXNSFFA069010）
国家自然科学青年基金项目"水下矢量声场高效稳健方位估计方法研究"(62301179). （62301179）
