激光与光电子学进展, 2021, 58 (6): 0610011, 网络出版: 2021-03-01
基于改进线性变换的迭代优化去雾算法 下载: 621次
Iterative Optimization Dehazing Algorithm Based on Improved Linear Transformation
图像处理 大气散射模型 图像去雾 迭代优化 线性变换 image processing atmospheric scattering model image dehazeing iterative optimization linear transformation
摘要
针对暗通道和线性变换算法的局限性,提出了一种基于改进线性变换的迭代优化去雾算法。首先,从最小颜色分量出发,建立大气耗散函数与最小颜色分量的自适应线性变换模型,以获得介质传输率的初始估计;然后,针对雾图中明亮区域的介质传输率进行自适应修正;其次,使用Kirsch和Laplacian算子构成的高阶滤波器进行迭代处理,得到最优介质传输率;最后,将优化后的介质传输率和基于四叉树子块搜索法获得的大气光值代入大气散射模型,得到复原图像。实验结果表明,本算法能恢复出清晰、自然的图像,对单幅图像的去雾效果较好。
Abstract
Aiming at the limitations of dark channel and linear transformation algorithm, an iterative optimization dehazing algorithm based on improved linear transformation is proposed in this work. First, starting from the minimum color component, the adaptive linear transformation model of the atmospheric dissipation function and the minimum color component is established to obtain the initial estimation of the medium transmission rate. Then, the medium transmission rate of the bright region in the fog image is adaptively modified. Second, the high-order filter composed of Kirsch and Laplacian operators is used for iterative processing to obtain the optimal medium transmission rate. Finally, the optimized medium transmission rate and the atmospheric light value obtained by quadtree sub block search method are substituted into the atmospheric scattering model to obtain the restored image. Experimental results show that the algorithm can restore the clear and natural image, and has good dehazing effect on a single image.
杨燕, 杜康, 武旭栋. 基于改进线性变换的迭代优化去雾算法[J]. 激光与光电子学进展, 2021, 58(6): 0610011. Yang Yan, Du Kang, Wu Xudong. Iterative Optimization Dehazing Algorithm Based on Improved Linear Transformation[J]. Laser & Optoelectronics Progress, 2021, 58(6): 0610011.