基于降质特性指标的水下光学图像增强  

Underwater Optical Image Enhancement Based on Degradation Characteristic Indices

作　　者：马金祥 范新南[2] 钱春俊 吴峰 相入喜 Ma Jinxiang;Fan Xinnan;Qian Chunjun;Wu Feng;Xiang Ruxi(School of Electrical and Information Engineering,Changzhou Institute of Technology,Changzhou 213032,Jiangsu,China;College of Information Science and Engineering,Hohai University,Changzhou 213200,Jiangsu,China)

机构地区：[1]常州工学院电气信息工程学院,江苏常州213032 [2]河海大学信息科学与工程学院,江苏常州213200

出　　处：《激光与光电子学进展》2024年第24期350-363,共14页Laser & Optoelectronics Progress

基　　金：国家自然科学基金青年科学基金(62201095,62101074);江苏省第六期“333高层次人才培养工程”;江苏省高等学校基础科学(自然科学)面上项目(21KJB110027);常州市科技计划(CE20225056);常州市领军型创新人才培育项目(CQ20210097);常州工学院教改专项课题(30120300100-23-zd-jgkt05)。

摘　　要：提出了一种基于降质特性指标的水下光学图像增强算法。首先,根据降质特性指标,判断原始图像存在哪些降质特性;然后,针对原始图像的降质特性,进行图像恢复处理;最后,应用有界广义对数比运算,进行图像增强处理。选取2类典型场景(辅助光源和自然光照)的水下降质光学图像作为研究对象,采用所提方法进行降质特性判断与图像增强处理。2幅图像的降质特性参数均恢复到合理范围,图像增强效果达到理想水平。当自适应梯度增益均值为1.5054时,中裂缝图像的光圈层最大亮度差由155下降到44,感知雾密度由2.38下降到0.37,动态范围比率由60.00%上升到76.08%,对比度由6.15提升到107.35;当自适应梯度增益均值为1.5678时,边坡图像的光圈层最大亮度差由65下降到24,感知雾密度由0.62下降到0.21,动态范围比率由29.41%上升到89.80%,颜色失真指标由0.66恢复到1.00,对比度由30.77提升到316.25。将所提算法与其他9种算法比较,结果显示所提算法在图像恢复与图像增强方面均具有明显优势。This paper proposed an underwater optical image enhancement algorithm based on degradation characteristic indices.First,this method determined the degradation characteristic present in the original image based on the these indices.Second,the image restoration process was performed according to the degradation characteristics of the original image.Finally,an image enhancement method was applied to the restored image using the bounded general logarithm ratio operation.The proposed algorithm was tested to identify degradation characteristics and enhance images in two typical underwater scenarios:one with auxiliary lighting and the other with natural lighting.Processing results showed that the degradation characteristic parameters were restored to a reasonable range,and the image enhancement effect reached an ideal level.For the middle crack image,with a mean adaptive gradient gain of 1.5054,the maximum brightness difference of the aperture layer decreased from 155 to 44,perceptual fog density reduced from 2.38 to 0.37,dynamic range ratio increased from 60.00%to 76.08%,and contrast increased from 6.15 to 107.35.For the slope image,with a mean adaptive gradient gain of 1.5678,the maximum brightness difference of the aperture layer decreased from 65 to 24,perceptual fog density decreased from 0.62 to 0.21,dynamic range ratio increased from 29.41%to 89.80%,color distortion index improved from 0.66 to 1.00,and contrast increased from 30.77 to 316.25.The proposed algorithm was compared with nine existing enhancement algorithms to evaluate its effectiveness.Results show that the proposed algorithm has advantages in terms of image restoration and enhancement.

关 键 词：水下图像增强 图像恢复 降质图像 有界广义对数比运算 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]