基于颜色校正和去模糊的水下图像增强方法

doi:10.11896/jsjkx.200800185

计算机科学 ›› 2021, Vol. 48 ›› Issue (4): 144-150.doi: 10.11896/jsjkx.200800185

• 计算机图形学&多媒体 • 上一篇下一篇

基于颜色校正和去模糊的水下图像增强方法

魏冬¹, 刘浩^1,2, 陈根龙¹, 宫晓蕙¹

1 东华大学信息科学与技术学院上海201620
2 人工智能教育部重点实验室上海200240

收稿日期:2020-06-24 修回日期:2020-09-22 出版日期:2021-04-15 发布日期:2021-04-09
通讯作者: 刘浩(liuhao@dhu.edu.cn)
基金资助:
上海市自然科学基金(18ZR1400300);人工智能教育部重点实验室开放基金

Underwater Image Enhancement Based on Color Correction and Deblurring

WEI Dong¹, LIU Hao^1,2, CHEN Gen-long¹, GONG Xiao-hui¹

1 College of Information Science and Technology,Donghua University,Shanghai 201620,China
2 Key Laboratory of Artificial Intelligence,Ministry of Education,Shanghai 200240,China

Received:2020-06-24 Revised:2020-09-22 Online:2021-04-15 Published:2021-04-09
About author:WEI Dong,born in 1997,postgraduate,is a member of China Computer Federation.His main research interests include underwater image enhancement and ima-ge quality evaluation.(1005689490@qq.com)
LIU Hao,born in 1977,associate professor,is a member of China Computer Federation.His main research interests include multimedia signal processing and intelligent sensing system.
Supported by:
Natural Science Foundation of Shanghai(18ZR1400300) and Foundation of Key Laboratory of Artificial Intelligence,Ministry of Education.

摘要/Abstract

摘要： 由于光在水下传播时会出现吸收和散射的情况,水下图像往往存在色偏、对比度低、模糊、光照不均匀等问题。根据水下图像成像模型,人们在海底拍摄所获得的图像往往是退化的图像,而退化的图像不能完整地表达海洋场景信息,难以满足实际的应用需要。为此,文中提出了一种基于颜色校正和去模糊的水下图像增强方法。该方法有效融合了颜色校正和去模糊两个阶段,取得了递增的增强效果。在颜色校正阶段,首先对原始图像进行对比度拉伸,在对比度拉伸完成之后,图像可能存在拉伸过度或拉伸不足的现象。因此,所提方法根据灰度世界先验,在对比度拉伸后进一步使用伽马校正来优化和调整图像的对比度和色彩,使图像的R,G,B三通道的灰度值之和趋于相等。接着,在去模糊阶段,通过融合暗通道先验对颜色校正后的图像进行去模糊,得到最终的增强图像。实验结果表明,所提方法具有良好的整体恢复效果,能有效地恢复图像信息,在主观评价和客观评价上均展现出较好的效果。另外,所提方法可以作为水下图像分类等计算机视觉任务的预处理步骤,在实验中能够将水下图像集的分类精度提升16%左右。

关键词: 对比度拉伸, 灰度世界, 去模糊, 水下图像, 图像分类, 颜色校正

Abstract: Due to the absorption and scattering of light when propagating underwater,underwater images often exhibit color shift,low contrast,blurry and uneven illumination.According to the imaging model of underwater image,many images from the seabed are often degraded severely,and these low-quality images cannot fully provide the ocean scene information,which is difficult to meet the practical application requirements.Therefore,this paper proposes an underwater image enhancement method based on color correction and deblurring.The proposed method effectively combines the two stages of both color correction and deblurring.During the color correction stage,the contrast of each original image is firstly stretched.After the contrast stretching is completed,some images may be overstretched or understretched.According to the gray world prior,after the contrast stretching,the gamma correction is further used to optimize and adjust the contrast and color of these images,so that the sum of the gray values from the R,G,and B channels of each image tends to be equal.Then,in the deblurring stage,it utilizes the dark channel prior to deblur the color-corrected image for the final enhanced image.Experimental results show that the proposed method has a good overall recovery effect,it can effectively restore image information,and obtain good enhancement performance in both subjective and objective evaluation.In addition,the proposed method can be used as a pre-processing step for computer vision tasks such as underwater image classification,and it can improve the classification accuracy of underwater image set by about 16% in our experiment.

Key words: Color correction, Contrast stretching, Deblurring, Gray world, Image classification, Underwater image

中图分类号:

TP391.41

魏冬, 刘浩, 陈根龙, 宫晓蕙. 基于颜色校正和去模糊的水下图像增强方法[J]. 计算机科学, 2021, 48(4): 144-150. https://doi.org/10.11896/jsjkx.200800185

WEI Dong, LIU Hao, CHEN Gen-long, GONG Xiao-hui. Underwater Image Enhancement Based on Color Correction and Deblurring[J]. Computer Science, 2021, 48(4): 144-150. https://doi.org/10.11896/jsjkx.200800185

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基于颜色校正和去模糊的水下图像增强方法

Underwater Image Enhancement Based on Color Correction and Deblurring

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