Underwater image clarifying based on human visual colour constancy using double-opponency  

作　　者：Bin Kong Jing Qian Pinhao Song Jing Yang Amir Hussain 

机构地区：[1]Institute of Intelligent Machines,Chinese Academy of Sciences,Hefei,China [2]Peng Cheng Laboratory,Shenzhen,China [3]Anhui Key Laboratory of Biomimetic Sensing and Advanced Robot Technology,Hefei,China [4]University of Science and Technology of China,Hefei,China [5]Peking University Shenzhen Graduate School,Shenzhen,China [6]Edinburgh Napier University,Edinburgh,Scotland

出　　处：《CAAI Transactions on Intelligence Technology》2024年第3期632-648,共17页智能技术学报（英文）

摘　　要：Underwater images are often with biased colours and reduced contrast because of the absorption and scattering effects when light propagates in water.Such images with degradation cannot meet the needs of underwater operations.The main problem in classic underwater image restoration or enhancement methods is that they consume long calcu-lation time,and often,the colour or contrast of the result images is still unsatisfied.Instead of using the complicated physical model of underwater imaging degradation,we propose a new method to deal with underwater images by imitating the colour constancy mechanism of human vision using double-opponency.Firstly,the original image is converted to the LMS space.Then the signals are linearly combined,and Gaussian convolutions are per-formed to imitate the function of receptive fields(RFs).Next,two RFs with different sizes work together to constitute the double-opponency response.Finally,the underwater light is estimated to correct the colours in the image.Further contrast stretching on the luminance is optional.Experiments show that the proposed method can obtain clarified underwater images with higher quality than before,and it spends significantly less time cost compared to other previously published typical methods.

关 键 词：COMPUTERS computer vision image processing image reconstruction 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]