基于改进多尺度Retinex理论的海上图像去雾算法

王宇勃; 甄荣

doi:10.3969/j.issn.1000-4653.2024.01.019

基于改进多尺度Retinex理论的海上图像去雾算法

王宇勃,
甄荣^,

集美大学航海学院, 福建厦门 361021

基金项目:

国家自然科学基金(52001134)

福建省自然科学基金(2020J01661)

详细信息

作者简介:
王宇勃(1999-)，男，硕士，研究方向为交通信息工程及控制、图像处理。E-mail:yubo990210@163.com

通讯作者:
甄荣(1990-)，男，博士，副教授，研究方向为海上智能交通。E-mail:zrandsea@163.com

中图分类号: U6-9
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- 文章访问数: 23
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出版历程
- 收稿日期: 2023-01-06

Marine image dehazing algorithm based on improved Multi-scale Retinex theory

WANG Yubo,
ZHEN Rong^,

Navigation College, Jimei University, Xiamen 361021, China

摘要

摘要: 针对传统去雾算法在海雾环境下处理得到的图像细节丢失、亮度偏暗及色彩失真等问题，提出了一种基于Retinex理论的海上图像去雾算法。首先，将图像转换到HSV空间，通过改进的多尺度Retinex增强算法对V通道单独处理获得照射分量。其次，将照射分量经过对数运算获得反射分量，与归一化处理后的H和S通道合并获得图像基础层。最后，通过引导滤波获得图像细节层，并与基础层合并进行自动白平衡处理，得到最终结果图像。试验证明，与暗通道先验算法及传统多尺度视网膜增强算法相比，提出的算法在标准差、平均梯度、峰值信噪比及结构相似性等评价指标方面均有所提升，海雾图像去雾质量得到有效增强，对提高海雾环境下船舶通航效率具有重要意义。
- Retinex理论 /
- 多尺度Retinex增强算法 /
- HSV空间 /
- 引导滤波 /
- 自动白平衡
Abstract: Conventional dehazing algorithm may cause detail loss, low brightness, and color distortion when it processes a marine image. A dehazing algorithm based on Retinex theory is introduced to solve the problems. The image is transformed into HSV（Hue-Saturation-Value） space before processing. The improved Multi-scale Retinex（MSR） algorithm is used to process V channel and obtain the illumination component. The reflex component is obtained by logarithmic operation. The latter is combined with the normalized H and S channel to obtain the image base layer. The image detail layer is obtained through guided filtering and combined with the base layer for automatic white balance processing to produce final result image. Experiments show that, compared to Dark Channel Prior algorithm and conventional MSR algorithm, the dehazed image produced by the improved MSR is superior in standard deviation, average gradient, peak signal to noise ratio and structural similarity.
- Retinex theory /
- MSR algorithm /
- HSV space /
- guided filtering /
- automatic white balance

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参考文献(16)

[1]	HU H M, GUO Q, ZHENG J, et al.Single image defogging based on illumination decomposition for visual maritime surveillance[J].IEEE Transactions on Image Processing, 2019, 28(6):2882-2897.
[2]	FEFILATYEV S, GOLDGOF D, SHREVE M, et al.Detection and tracking of ships in open sea with rapidly moving buoy-mounted camera system[J].Ocean Engineering, 2012, 54:1-12.
[3]	高志远, 詹文强, 元海文.面向无人船的天空区域检测算法[J].中国航海, 2021, 44(4):101-106.GAO Z Y, ZHAN W Q, YUAN H W.Sky area detection algorithm for USV[J].Navigation of China, 2021, 44(4):101-106.(in Chinese)
[4]	王炳德, 杨柳涛.基于YOLOv3的船舶目标检测算法[J].中国航海, 2020, 43(1):67-72.WANG B D, YANG L T.Ship target detection algorithm based on YOLOv3[J].Navigation of China, 2020, 43(1):67-72.(in Chinese)
[5]	郑凤仙, 王夏黎, 何丹丹, 等.单幅图像去雾算法研究综述[J].计算机工程与应用, 2022, 58(3):1-14.ZHENG F X, WANG X L, HE D D, et al.Survey of single image defogging algorithm[J].Computer Engineering and Applications, 2022, 58(3):1-14.(in Chinese)
[6]	HE K M, SUN J, TANG X O.Single image haze removal using Dark Channel Prior[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12):2341-2353.
[7]	杨哲, 邵哲平.基于自适应小波阈值与曲波变换的SAR图像去噪[J].中国航海, 2020, 43(4):46-51.YANG Z, SHAO Z P.SAR image denoising based on adaptive wavelet threshold and curvelet transform[J].Navigation of China, 2020, 43(4):46-51.(in Chinese)
[8]	JOBSON D J, RAHMAN Z, WOODELL G A.Properties and performance of a center/surround Retinex[J].IEEE Transactions on Image Processing, 1997, 6(3):451-462.
[9]	RAHMAN Z, JOBSON D J, WOODELL G A.Multi-scale Retinex for color image enhancement[C]//Proceedings of 3rd IEEE International Conference on Image Processing.Lausanne:IEEE, 1996.
[10]	JOBSON D J, RAHMAN Z, WOODELL G A.A multiscale Retinex for bridging the gap between color images and the human observation of scenes[J].IEEE Transactions on Image Processing, 1997, 6(7):965-976.
[11]	XU J, HOU Y K, REN D W, et al.STAR:a structure and texture aware Retinex model[J].IEEE Transactions on Image Processing, 2020, 29:5022-5037.
[12]	史瑞雪.基于Retinex理论的雾霾天气图像增强算法研究[D].太原:太原理工大学, 2021.SHI R X.Research on image enhancement algorithm of haze weather based on Retinex theory [D].Taiyuan:Taiyuan University of Technology, 2021.(in Chinese)
[13]	张航瑛, 王雪琦, 王华英, 等.基于明度分量的Retinex-Net图像增强改进方法[J].物理学报, 2022, 71(11):101-109.ZHANG H Y, WANG X Q, WANG H Y, et al.Advanced Retinex-Net image enhancement method based on value component processing [J].Acta Physica Sinica, 2022, 71(11):101-109.(in Chinese)
[14]	陈文艺, 杨承勋, 杨辉.引导滤波和对数变换算法融合的多尺度Retinex红外图像增强[J].红外技术, 2022, 44(4):397-403.CHEN W Y, YANG C X, YANG H.Multi-scale Retinex infrared image enhancement based on the fusion of guided filtering and logarithmic transformation algorithm[J].Infrared Technology, 2022, 44(4):397-403.(in Chinese)
[15]	HE K M, SUN J, TANG X O.Guided image filtering[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6):1397-1409.
[16]	陶冶, 许文海, 徐鲁强, 等.基于人工欠曝光融合和白平衡技术的水下图像增强算法[J].计算机应用, 2021, 41(12):3672-3679.TAO Y, XU W H, XU L Q, et al.Underwater image enhancement algorithm based on artificial under-exposure fusion and white-balancing technique[J].Journal of Computer Applications, 2021, 41(12):3672-3679.(in Chinese)