Single image defogging based on particle swarm optimization  

作　　者：郭璠 周聪 刘丽珏 唐琎 

机构地区：[1]School of Information Science and Engineering, Central South University, Changsha 410083, China

出　　处：《Optoelectronics Letters》2017年第6期452-456,共5页光电子快报（英文版）

基　　金：supported by the National Natural Science Foundation of China(Nos.61573380 and 61502537);the Postdoctoral Science Foundation of Central South University

摘　　要：Due to the lack of enough information to solve the equation of image degradation model, existing defogging methods generally introduce some parameters and set these values fixed. Inappropriate parameter setting leads to difficulty in obtaining the best defogging results for different input foggy images. Therefore, a single image defogging algorithm based on particle swarm optimization(PSO) is proposed in this letter to adaptively and automatically select optimal parameter values for image defogging algorithms. The proposed method is applied to two representative defogging algorithms by selecting the two main parameters and optimizing them using the PSO algorithm. Comparative study and qualitative evaluation demonstrate that the better quality results are obtained by using the proposed parameter selection method.

关 键 词：SWARM REPRESENTATIVE AUTOMATICALLY qualitative letter selecting DIFFICULTY ITERATION VISIBILITY removed 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]