基于背景光估计与颜色修正的水下图像增强  

Underwater Image Enhancement Based on Background Light Estimation and Color Correction

作　　者：王红茹[1,2] 张弓 卢道华[1,2,3] 王佳 WANG Hongru;ZHANG Gong;LU Daohua;WANG Jia(School of Mechanical Engineering,Jiangsu University of Science and Technology,Zhenjiang,Jiangsu 212003,China;Key Laboratory of Advanced Manufacture and Process for Marine Mechanical Equipmentin Jiangsu Province,Jiangsu University of Science and Technology,Zhenjiang,Jiangsu 212003,China;Marine Equipment Research Institute,Jiangsu University of Science and Technology,Zhenjiang,Jiangsu 212003,China)

机构地区：[1]江苏科技大学机械工程学院,江苏镇江212003 [2]江苏科技大学江苏省船海机械先进制造及工艺重点实验室,江苏镇江212003 [3]江苏科技大学海洋装备研究院,江苏镇江212003

出　　处：《计算机工程》2020年第10期253-258,共6页Computer Engineering

基　　金：国家重点研发计划“船载无人潜水器收放系统”(2018YFC0309100);江苏省船海机械先进制造及工艺重点实验室开放基金(ZDKT18-06)。

摘　　要：针对水下成像过程中的图像降质和颜色衰减现象,提出一种基于全局背景光估计和颜色校正的图像增强算法。利用雾图像和水下图像的相似性对空气中的去雾算法进行改进,在估计图像全局背景光时选取矩形模板对图像分块计算色彩饱和度方差,选取方差最小的区域作为背景光的预估图像。针对原始的背景光估计方法所得图像偏白的问题,通过最小值滤波处理,同时利用Retinex算法校正图像R通道的颜色,再结合各颜色通道的色彩衰减系数比得到其他通道图。实验结果表明,该算法能有效去除水下图像的浑浊部分,改善图像的偏色问题,使图像清晰度得到明显提升。To solve the problem of image degradation and color attenuation in underwater imaging,this paper proposes an image enhancement algorithm based on global background light estimation and color correction.The similarity between fog image and underwater image is used to improve the algorithm of fog removal in air.When estimating the global background light of the image,the rectangular template is selected to calculate the color saturation variance in image blocks,and the region with the minimum variance is selected as the estimated image of background light.To address the problem that the original background light estimation algorithm will make the image whiter than it should be,the minimum filtering is implemented.Also,the Retinex algorithm is used to correct the color of R channel of the image and then other channel graphs are obtained by combining the color attenuation coefficient ratio of each color channel.Experimental results show that this algorithm can effectively remove the turbidity of underwater images improve the color deviation of images,and significantly improve the clarity of images.

关 键 词：水下图像增强 暗原色先验 背景光估计 颜色校正 色彩饱和度方差 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]