提出了一种基于高斯衰减的自适应线性变换图像去雾算法。建立有雾图像与无雾图像最小值通道之间的线性变换模型,利用有雾图像最小值通道构造高斯函数以自适应补偿估计图像明亮区域的透射率,提升透射率的准确度。根据大气散射模型复原图像,使用交叉双边滤波器消除透射率纹理效应。实验结果表明,所提算法能有效地改善图像明亮区域的色彩失真,消除景深边缘Halo效应,所复原的图像具有明显的细节和适宜的饱和度。

An adaptive linear transformation image dehazing algorithm based on Gaussian attenuation is proposed. A linear transformation model between the minimum channel of hazy images and that of haze-free images is established. A Gaussian function using the minimum channel of hazy images is constructed to adaptively compensate the transmissivity in the bright region and improve the accuracy of transmissivity. A cross-bilateral filter is used to eliminate the texture effects of transmission, and the image is restored by the atmospheric scattering model. The experimental results show that the proposed algorithm can effectively improve color distortion in the bright regions of images and eliminate the Halo effect at the edge of depth of field. Moreover, the restored image possesses obvious details and suitable saturation.