文献类型：期刊文献

英文题名：Efficient image dehazing algorithm using multiple priors constraints

作者：Huang, Zilong[1];Jing, Hongyuan[1,2];Chen, Aidong[1,2,3];Hong, Chen[1,3];Shang, Xinna[1,2,3]

第一作者：Huang, Zilong

通讯作者：Jing, HY[1]

机构：[1]Beijing Union Univ, Coll Robot, Beijing 100101, Peoples R China;[2]Coll Robot, Beijing Key Lab Informat Serv Engn, Beijing 100101, Peoples R China;[3]Beijing Union Univ, Multiagent Syst Res Ctr, Beijing 100101, Peoples R China

第一机构：北京联合大学机器人学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Robot, Beijing 100101, Peoples R China.|[1141739]北京联合大学机器人学院;[11417]北京联合大学;

年份：2023

卷号：90

外文期刊名：JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION

收录：;EI(收录号：20224913204075);Scopus(收录号：2-s2.0-85143052042);WOS:【SCI-EXPANDED(收录号:WOS:000906875200007)】；

语种：英文

外文关键词：Image dehazing; Atmospheric scattering model; Atmospheric light estimation; Multiple prior constraints

摘要：In this study, a robust and efficient image dehazing technique based on the atmospheric scattering model is proposed, which effectively overcomes the limitations of a single prior condition. It is composed of a transmission estimation module and an atmospheric light estimation module. The transmission estimation module integrates multiple dehazing prior strategies and effectively optimises transmission estimation and application range. The atmospheric light estimation module uses the fuzzy C-means clustering algorithm (FCM) to estimate the atmospheric light of different scenes in an image. Unlike in the previous work, the atmospheric light in this module is a nonglobal value, and a pixel-level atmospheric light value matrix is obtained. Numerous experiments show that the proposed dehazing algorithm is superior to state-of-the-art methods.