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 ...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.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61573380 and 61502537)the Postdoctoral Science Foundation of Central South University
文摘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.
