基于L1范式优化透射率和饱和度补偿的去雾方法

Defogging Method Based on L1 Paradigm Optimized Transmittance and Saturation Compensation

雾霾天气下捕获的图像存在低饱和度与色调偏移等现象,传统的暗通道先验去雾算法在处理有雾图像时各有不足。为此,提出一种基于L1范式优化透射率和饱和度补偿的图像去雾方法。首先,利用交叉双边滤波器对大气光值进行区间估计,并通过引导滤波方法获得介质传输率的粗略估计;然后,利用Kirsch与Laplacian算子构成的一组高阶滤波器对透射率进行处理,同时通过L1范式对目标函数进行优化,从而得到优化后的透射率;最后,根据饱和度补偿与色调调整对图像进行细节处理,获得无雾的清晰图像。根据提出的模型对单幅图像进行去雾处理,并分析该方法的效率与误差。实验表明,该方法处理的图像具有最佳的视觉效果,相比于其他方法,图像边缘细节信息明显,且具有较快的运算速度;采用饱和度补偿与色调调整可以在避免颜色畸变的同时获得高饱和度与高对比度的复原图像,鲁棒性较好。

The images captured in smoggy weather feature low saturation and hue shift.The traditional dark channel prior defogging algorithms are not efficient when dealing with foggy images.Therefore,an image deazing method based on L1 paradigm optimized transmittance and saturation compensation was proposed.Firstly,the cross-bilateral filter was used to estimate the interval of the atmospheric light value,and the initial weight of the medium transmission rate was obtained by the guided filtering method.Then,a set of high-order filters composed of Kirsch and Laplacian operators were used to process the transmittance.The final transmittance value was obtained after the optimization of the objective function by the L1 paradigm.Finally,the image was further modified by the saturation compensation method.Based on the atmospheric scattering model and the tone adjustment,the foggy image was restored.Single images were defogged by using the proposed method.The efficiency and error of the proposed method were analyzed.The results of the experiments with the proposed method and several other algorithms show that the proposed method has the best visual effect in restoring images,with clear image edge detail information and fast calculation speed.High saturation and high contrast images can be restored by saturation compensation and tone adjustment while avoiding color distortion.The proposed method also has good robustness.