基于边缘保持的自适应高斯衰减去雾算法

Adaptive Gaussian Attenuation Defogging Algorithm Based on Edge Preservation

针对通过局部相似假设估计透射率,景深突变边缘出现Halo效应问题,提出一种基于边缘保持的自适应高斯衰减图像去雾算法。该方法从大气散射模型出发,引入大气幕亮度,将场景透射率的估计等效为大气幕亮度的估计。通过边缘检测算子提取边缘信息,分离边缘区域与非边缘区域,利用邻域内像素点的空间邻近度构建自适应高斯函数对非边缘区域进行平滑衰减,从而获得最优效果。通过大量实验对所提方法进行验证,结果表明复原的图像整体平滑,细节明显,有效地消除景深突变处的Halo效应,并且在客观评价中也体现出了优势。

An adaptive Gaussian attenuation image defogging algorithm based on edge preservation is proposed to solve the problem when transmissivity is estimated under the local similarity assumption,the abrupt change edge of depth field often leads to the Halo effect.This method starts from the atmospheric scattering model and introduces the luminance of the sky,the estimation of scene transmissivity can be equivalent to the estimation of the luminance of the sky.The edge information is extracted by the edge detection operator to separate the edge region and the nonedge region.The adaptive Gaussian function is constructed by using the spatial proximity of the pixel points in the neighborhood to smooth and attenuation on the non-edge region,thereby obtaining the optimal effect.Through a large number of experiments to verify the proposed method,the results show that the restored image is smooth and the details are obvious.It can effectively eliminate the Halo effects at the abrupt changes of the depth field,and it also shows its advantages in the objective evaluation.