《计算机应用》唯一官方网站 ›› 2021, Vol. 41 ›› Issue (12): 3672-3679.DOI: 10.11772/j.issn.1001-9081.2021010065

• 多媒体计算与计算机仿真 • 上一篇    

基于人工欠曝光融合和白平衡技术的水下图像增强算法

陶冶1,2(), 许文海1, 徐鲁强2, 郭富城2, 蒲海波2, 陈广同2   

  1. 1.大连海事大学 信息科学技术学院,辽宁 大连 116026
    2.辽宁港口集团有限公司 专业能力中心,辽宁 大连 116001
  • 收稿日期:2021-01-13 修回日期:2021-04-07 接受日期:2021-04-20 发布日期:2021-06-04 出版日期:2021-12-10
  • 通讯作者: 陶冶
  • 作者简介:许文海(1956—),男,黑龙江哈尔滨人,教授,博士,主要研究方向:数字图像处理、高分辨率成像系统设计
    徐鲁强(1981—),男,辽宁大连人,高级工程师,硕士,主要研究方向:港口设施管理
    郭富城(1995—),男,辽宁大连人,助理工程师,主要研究方向:港口技术管理
    蒲海波(1968—),男,湖北宜昌人,高级工程师,硕士,主要研究方向:港口技术管理
    陈广同(1963—),男,辽宁营口人,高级工程师,硕士,主要研究方向:港口技术管理。
  • 基金资助:
    国家重点研发计划项目(2019YFB1600400);国家自然科学基金资助项目(61701069)

Underwater image enhancement algorithm based on artificial under-exposure fusion and white-balancing technique

Ye TAO1,2(), Wenhai XU1, Luqiang XU2, Fucheng GUO2, Haibo PU2, Guangtong CHEN2   

  1. 1.Information Science and Technology College,Dalian Maritime University,Dalian Liaoning 116026,China
    2.Professional Competence Centre,Liaoning Port Group Company Limited,Dalian Liaoning 116001,China
  • Received:2021-01-13 Revised:2021-04-07 Accepted:2021-04-20 Online:2021-06-04 Published:2021-12-10
  • Contact: Ye TAO
  • About author:XU Wenhai, born in 1956, Ph. D., professor. His research interests include digital image processing, design of high-resolution imaging system.
    XU Luqiang, born in 1981, M. S., senior engineer. His research interests include port facility management.
    GUO Fucheng, born in 1995, assistant engineer. His research interests include port technology management.
    PU Haibo, born in 1968, M. S., senior engineer. His research interests include port technology management.
    CHEN Guangtong, born in 1963, M. S., senior engineer. His research interests include port technology management.
  • Supported by:
    the National Key Research and Development Program of China(2019YFB1600400);the National Natural Science Foundation of China(61701069)

摘要:

获得清晰准确的水下图像是人类探索水下世界的重要前置条件。然而与平常图像相比,水下图像往往具有对比度低、细节保留不足及颜色失真等问题,这导致其视觉效果不佳。针对上述问题,提出了基于人工欠曝光融合和白平衡技术(AUF+WB)的水下图像增强算法。首先,利用调节伽马值的方式对原始水下图像进行操作,从而生成5幅相应的欠曝光图像;然后,以对比度、饱和度及良好曝光度作为融合权重,并结合多尺度融合来生成融合图像;最后,将各类颜色通道补偿后的图像分别结合灰色世界假设白平衡生成相应的白平衡图像,再利用水下彩色图像质量评价指标(UCIQE)及水下图像质量评价标准(UIQM)对得到的白平衡图像进行评价。通过选取不同类型的水下图像作为实验样本,将AUF+WB算法与现存先进的水下图像去雾算法进行比较,结果表明AUF+WB算法在图像质量定性、定量两方面分析中和对比算法相比均有更好的表现。所提出的AUF+WB算法可矫正水下图像的颜色失真,并增强其对比度、恢复其细节,有效提升了水下图像的视觉质量。

关键词: 水下图像, 图像增强, 图像融合, 伽马矫正, 白平衡

Abstract:

Acquisition of clear and accurate underwater images is an important prerequisite to help people explore the underwater world. However, compared with regular images, underwater images always have problems such as low contrast, detail loss and color distortion, resulting in bad visual effect. In order to solve the problems, a new underwater image enhancement algorithm based on Artificial Under-exposure Fusion and White-Balancing technique (AUF+WB) was proposed. Firstly, the Gamma correction operation was used to process the original underwater image and generate 5 corresponding under-exposure images. Then, the contrast, saturation and well-exposedness were employed as fusion weights, and the multi-scale fusion method was combined to generate the fused image. Finally, the images compensated by various color channels were combined with the Gray-World white balance assumption respectively to generate the corresponding white balance images, and these obtained white balance images were evaluated by using the Underwater Color Image Quality Evaluation (UCIQE) and the Underwater Image Quality Measure (UIQM). With selecting different types of underwater images as experimental samples, the proposed AUF+WB algorithm was compared with the existing state-of-the-art underwater image defogging algorithms. The results show that, the proposed AUF+WB algorithm has better performance than the comparison algorithms on both qualitative and quantitative analysis of image quality. The proposed AUF+WB algorithm can effectively improve the visual quality of underwater images by removing color distortion, enhancing contrast, and recovering details of underwater images.

Key words: underwater image, image enhancement, image fusion, Gamma correction, white balance

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