Underwater Diver Image Enhancement via Dual-Guided Filtering  

作　　者：Jingchun Zhou Taian Shi Weishi Zhang Weishen Chu 

机构地区：[1]College of Information Science and Technology,Dalian Maritime University,Dalian,116026,China [2]Department of Computer and Information Science,University of Pennsylvania,Philadelphia,PA 19104,USA

出　　处：《Computer Modeling in Engineering & Sciences》2022年第5期1063-1081,共19页工程与科学中的计算机建模（英文）

基　　金：National Natural Science Foundation of China(No.61702074);the Liaoning Provincial Natural Science Foundation of China(No.20170520196);the Fundamental Research Funds for the Central Universities(Nos.3132019205 and 3132019354).

摘　　要：The scattering and absorption of light propagating underwater cause the underwater images to present lowcontrast,color deviation,and loss of details,which in turn make human posture recognition challenging.To address these issues,this study introduced the dual-guided filtering technique and developed an underwater diver image improvement method.First,the color distortion of the underwater diver image was solved using white balance technology to obtain a color-corrected image.Second,dual-guided filtering was applied to the white balanced image to correct the distorted color and enhance its details.Four feature weight maps of the two images were then calculated,and two normalizedweightmapswere constructed formulti-scale fusion using normalization.To better preserve the obtained image details,the fusion image was histogram-stretched to obtain the final enhanced result.The experimental results validated that this method has improved the accuracy of underwater human posture recognition.

关 键 词：Multi-scale fusion image enhancement guided filter underwater diver images 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]