天空区域分割修正的图像去雾新算法

Novel image defogging algorithm for sky region segmentation correction

为了改进基于暗通道先验假设图像去雾算法的细节信息丢失、大气光强值估计偏低、天空区域去雾效果不佳等不足,笔者提出一种天空区域分割修正的彩色图像去雾新算法。新算法在暗通道先验算法的基础上,对暗通道与亮通道先验模型进行带参线性加权运算,提出加权平均融合COPLIP模型和MSR模型的天空区域修正新模型及实现算法。与现有去雾算法比较,实验结果表明新算法能够克服现有算法对于天空区域去雾效果不佳的问题,同时通过客观评价指标验证了新算法的有效性。

In order to solve the problems of the detailed information loss,the low atmospheric light intensity estimation and the poor defogging effect in the sky region based on the dark channel prior image defogging algorithm,this paper proposes a new color image defogging algorithm for sky region segmentation correction.Based on the dark channel prior algorithm,the dark channel and bright channel prior model is linearly weighted with a parameter.This paper also proposes a new sky region correction model based on weighted average fusion of the COPLIP model and the MSR model.Compared with the existing dehazing algorithm,experimental results show that the new algorithm can overcome the problem of poor effect in the sky region.In addition,the paper also validates the effectiveness of the new algorithm by objective evaluation indicators.