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结合色彩补偿与双背景光融合的水下图像复原OA北大核心CSTPCD

Underwater image restoration method combining color compensation and dual background light fusion

中文摘要英文摘要

针对复杂成像环境下,水下图像存在颜色失真、细节模糊以及对比度低的问题,提出结合色彩补偿与双背景光融合的水下图像复原方法.通过分析光在水中的吸收衰减特性,提出改进的水下成像模型,基于Retinex理论与白平衡算法引入色彩补偿分量,降低水体背景颜色影响;根据背景光强度和颜色分布特性,提出双候选背景光融合方法,准确估计全局背景光;不依赖任何水体环境参数,根据背景颜色与散射系数的内在关系,采用引导-高通滤波,优化并增强各通道透射率;最后,逆求解成像模型复原水下图像.实验结果表明,在4个不同的水下数据集上与经典及新颖方法对比,所提方法恢复的图像颜色更自然,纹理细节更丰富清晰;色差值改善幅度达 5.4%,UCIQE及FDUM指标提升幅度分别达8.3%和4.5%.所提方法在定性和定量实验中更具优势,能够显著提高水下图像质量.

To address the challenges of color distortion,blurred details,and low contrast in underwater images caused by complex imaging environments,a novel restoration method that integrates color compen-sation with dual background light fusion is introduced.This method begins by enhancing the traditional un-derwater imaging model to reflect light absorption and attenuation in water more accurately.It incorporates a color compensation technique inspired by Retinex theory and white balance algorithms to mitigate the im-pact of the water's background color.A novel dual-candidate background light fusion approach is then de-veloped to precisely estimate the global background light,considering the intensity and color distribution of background light.This is followed by the use of guided high-pass filtering to refine and boost the transmis-sion across each channel,leveraging the connection between the water's background color and the scatter-ing coefficient,without relying on specific water environment parameters.The method concludes with the restoration of the underwater image through the reverse application of the imaging model.Testing on four diverse underwater datasets has shown that this approach surpasses several classic and advanced methods,delivering images with more natural colors and enhanced,clearer textures.The color difference value im-proved by 5.4%,while the UCIQE and FDUM metrics increase by 8.3%and 4.5%respectively,under-scoring the method's effectiveness in both qualitative and quantitative evaluations and its significant contri-bution to enhancing the quality of underwater imagery.

林森;查子月

沈阳理工大学 自动化与电气工程学院,辽宁 沈阳 110159

计算机与自动化

水下图像复原色彩补偿背景光融合透射率估计

underwater image restorationcolor compensationbackground light fusiontransmission es-timation

《光学精密工程》 2024 (007)

1059-1074 / 16

国家重点研发计划资助项目(No.2018YFB1403303);辽宁省教育厅高等学校基本科研项目(No.LJK-MZ20220615)

10.37188/OPE.20243207.1059

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