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基于优势特征图像融合的水下光学图像增强
Alternative TitleUnderwater Optical Image Enhancement Based on Dominant Feature Image Fusion
林森1,2,3; 迟凯晨1; 李文涛2,3; 唐延东2,3
Department机器人学研究室
Source Publication光子学报
ISSN1004-4213
2020
Volume49Issue:3Pages:1-13
Indexed ByEI ; CSCD
EI Accession number20201508406656
CSCD IDCSCD:6685824
Contribution Rank1
Funding Organization国家自然科学基金(Nos.91648118,61473280) ; 辽宁省自然基金面上项目(No.2015020100) ; 辽宁省教育厅科研项目(No.LJ2019JL022) ; 辽宁省自然科学基金指导计划项目(No.2019-ZD-0038)
Keyword数字图像处理 图像增强 图像融合 水下图像 海洋光学 水下成像系统
Abstract

针对水下光学图像颜色失真、非均匀光照、对比度低的问题,提出基于优势特征图像融合的水下光学图像增强算法.首先,提出改进的暗通道先验算法去除退化图像中的不均匀浑浊并均衡色彩;其次,对颜色校正图像分别使用基于加权分布的自适应伽玛校正算法和限制对比度自适应直方图均衡-同态滤波算法,增强颜色校正图像对比度并使其亮度均衡;最后,定义三幅融合图像即颜色校正图像、亮度均衡图像、对比度增强图像的关联权重图,通过多尺度融合算法获得融合图像.与单一预处理算法只能解决对应的退化现象相比,该算法对单幅退化图像进行多算法处理,得到三幅优势特征图像,通过不同权重的组合最大程度地将各优势特征相结合,得到的综合效果远超各单一算法优化效果,不再局限于解决颜色失真等单一问题.将本文算法与现有算法在主观评价和客观评价两方面进行实验对比,结果表明,该算法可以有效平衡水下图像的色度、饱和度及清晰度,视觉效果接近自然场景下的图像.

Other Abstract

Aiming at the problems of color distortion, uneven illumination and low contrast of underwater optical image, an underwater optical image enhancement algorithm based on the fusion of dominant feature image was proposed. Firstly, an improved dark channel prior algorithm was proposed to remove the uneven turbidity and balance the color in the degraded image. Secondly, the adaptive gamma correction algorithm based on weighted distribution and the contrast limited adaptive histogram equalization-homomorphic filtering algorithm were used to enhance the contrast of color correction image and make its brightness distribution uniform. Finally, the associated weight maps of the three fused images namely the color-corrected image, the brightness-balanced image and the contrast-enhanced image were defined, and the fused images were obtained by the multi-scale fusion algorithm. Compared with single preprocessing algorithm which can only solve the corresponding degradation phenomenon, the algorithm processes single degraded image with multiple algorithms and obtains three dominant feature images, the combination of different weight scan combine the dominant features to the greatest extent, and the comprehensive effect is far beyond the optimization effect of each single algorithm, and is no longer limited to solving single problems such as color distortion. The algorithm in this paper is compared with existing algorithms in subjective evaluation and objective evaluation. The results show that the algorithm can effectively balance the chroma, saturation and sharpness of underwater images, and the visual effect is close to the images in natural scenes.

Language中文
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/26551
Collection机器人学研究室
Corresponding Author林森
Affiliation1.辽宁工程技术大学电子与信息工程学院
2.中国科学院沈阳自动化研究所机器人学国家重点实验室
3.中国科学院机器人与智能制造创新研究院
Recommended Citation
GB/T 7714
林森,迟凯晨,李文涛,等. 基于优势特征图像融合的水下光学图像增强[J]. 光子学报,2020,49(3):1-13.
APA 林森,迟凯晨,李文涛,&唐延东.(2020).基于优势特征图像融合的水下光学图像增强.光子学报,49(3),1-13.
MLA 林森,et al."基于优势特征图像融合的水下光学图像增强".光子学报 49.3(2020):1-13.
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