应用光学, 2019, 40 (3): 447, 网络出版: 2019-06-10   

一种自适应线性透射率估计去雾算法

Adaptive linear transmission estimation dehazing algorithm
作者单位
兰州交通大学 电子与信息工程学院,甘肃 兰州 730070
摘要
为了有效复原雾霾天气下退化的图像,文章提出了一种自适应线性透射率估计去雾算法。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;利用有雾图像的混合通道得到自适应参数,结合自适应参数和线性变换模型估计出透射率,通过有雾图像的最小值通道构造高斯函数来补偿估计明亮区域透射率,提升该区域透射率的准确度,再使用交叉双边滤波器消除纹理效应得到优化透射率;最后,结合大气散射模型复原出无雾图像。实验结果表明,该方法有效降低了时间复杂度,且复原的图像细节明显,明亮度适宜。
Abstract
In order to effectively restore the degraded images in hazy weather, an adaptive linear transmission estimation dehazing algorithm was proposed. Firstly, we created a linear transformation model between the hazy image and the dehazing image minimum channel. Secondly, the adaptive parameters were obtained by using the mixed channel of the hazy image, and the transmission was estimated by combining the adaptive parameter and the linear transformation model. Then, a Gaussian function was constructed by the minimum channel of the hazy image to compensate the estimated transmission of the bright region, and the accuracy of the transmission of this region was improved, and the cross-bilateral filter was used to eliminate the texture effect to obtain the optimized transmission. Finally, a dehazing image was restored in combination with the atmospheric scattering model. The experimental results show that the method can effectively reduce the time complexity, and the restored image has obvious details and appropriate brightness.

杨燕, 李一菲, 岳辉. 一种自适应线性透射率估计去雾算法[J]. 应用光学, 2019, 40(3): 447. YANG Yan, LI Yifei, YUE Hui. Adaptive linear transmission estimation dehazing algorithm[J]. Journal of Applied Optics, 2019, 40(3): 447.

本文已被 3 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!