自动化学报2016，Vol.42Issue(9)：1367-1379,13.DOI:10.16383/j.aas.2016.c150525
基于雾气浓度估计的图像去雾算法
Image Haze Removal Algorithm Based on Haze Thickness Estimation
摘要
Abstract
This paper proposes a haze thickness estimation model based on visual characteristics of haze thickness, and combines this model with atmosphere scattering model to present an innovative image dehazing algorithm. First, a haze thickness quantitative map is calculated via the haze thickness estimation model, from which the thickest area is identified by the fuzzy clustering algorithm and global atmospheric light is estimated. After that, the algorithm carries on clustering processing towards the non-thickest area in the quantitative map, and estimates the transmission of each cluster unit according to the optimized transmission evaluation index mentioned in this paper. The haze-free image can be restored from scattering model with global light, refined transmission map and original hazy image. At last, we propose a multi-scale sharpening algorithm based on wavelet domain to make up for the defect that the haze-free image is dark-look so as to improve the visual effect. Several numerical experiments demonstrate that the proposed method outperforms the mainstream dehazing algorithms in daze removal effect at a much lower implementation cost.关键词
图像去雾/模糊聚类/雾气浓度估计模型/导向滤波器/大气散射模型Key words
Image daze removal/fuzzy clustering/haze thickness estimation model/guided filter/atmosphere scattering model引用本文复制引用
鞠铭烨,张登银,纪应天..基于雾气浓度估计的图像去雾算法[J].自动化学报,2016,42(9):1367-1379,13.基金项目
国家自然科学基金(61571241),江苏省高校自然科学研究重大项目(15KJA510002),江苏省产学研前瞻性联合研究项目(BY2014014)资助Supported by National Natural Science Foundation of China (61571241), Key University Science Research Project of Jiangsu Province (15KJA510002), and Prospective Joint Research Project of Jiangsu Province (BY2014014) （61571241）
