基于Lab色彩空间的沙尘降质图像增强方法  

Sand-dust image enhancement based on Lab color space

作　　者：牛宏侠 张鸿铸[2,3] NIU Hongxia;ZHANG Hongzhu(School of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Key Laboratory of Plateau Traffic Information Engineering and Control of Gansu Province,Lanzhou Jiaotong University,Lanzhou 730070,China;Key Lab of Opt-Electronic Technology and Intelligent Control of Ministry of Education,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学自动化与电气工程学院,甘肃兰州730070 [2]兰州交通大学甘肃省高原交通信息工程及控制重点实验室,甘肃兰州730070 [3]兰州交通大学光电技术与智能控制教育部重点实验室,甘肃兰州730070

出　　处：《液晶与显示》2024年第9期1274-1284,共11页Chinese Journal of Liquid Crystals and Displays

基　　金：甘肃省自然科学基金(No.22JR5RA358);兰州市人才创新创业项目(No.2022-RG-56);甘肃省重点研发项目计划-工业类项目(No.23YFGA0049)。

摘　　要：针对沙尘天气导致的数字图像质量大幅下降问题,提出一种基于Lab色彩空间的沙尘降质图像增强方法。将沙尘图像增强分解为偏色校正与细节增强两个步骤处理。偏色校正部分包括去除色偏与亮度拉伸。首先对Lab与YUV色彩空间中的沙尘图像直方图偏移特点进行了分析,然后提出一种Lab空间偏色校正算法修正直方图偏移,并对初步去除偏色的图像进行亮度拉伸,提升图像对比度。在细节增强部分,引入一种基于饱和度估计透射率的去雾方法进一步增强图像细节信息。实验结果表明,相较于各对比算法,所提算法可以去除不同程度沙尘带来的色偏,且在面对中小型图像时具有最佳的时间性能表现。在量化指标方面,基于无参考感知的图像质量评估标准和基于熵的无参考图像质量评价标准分别提升了3.2%和10.7%。本文方法可以有效去除色偏,还原清晰图像。To address the severe degradation in image quality caused by sand and dust weather conditions,a sand and dust image enhancement method based on the Lab color space is proposed.The enhancement process is decomposed into two steps:color correction and detail enhancement.The color correction part includes color bias removal and brightness stretching.Firstly,the shift characteristics of the sand and dust image histograms in the Lab and YUV color spaces are studied.Then,a Lab space color correction algorithm is proposed to correct the histogram shift,and brightness stretching is applied to enhance the image contrast after color bias removal.For detail enhancement,a haze removal method based on the estimation transmission map of saturation is introduced to further enhance the image’s detail information.Experimental results indicate that compared to other algorithms,the proposed algorithm can effectively remove the color bias brought by sand and dust at different levels,and demonstrates the best performance in terms of time efficiency for small and medium-sized images.In terms of quantitative evaluation,the method proposed in this paper achieves a 3.2%improvement based on a no-reference perception-based image quality evaluator and a 10.7%improvement based on an entropy-based no-reference image quality assessment.Therefore,it can effectively remove the color bias and restore clear images.

关 键 词：图像增强 沙尘图像 Lab色彩空间 偏色校正 图像去雾 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]