摘要
针对雾霾天气条件下的图像降质问题,提出一种高效的清晰化算法。利用最小值运算与形态学操作分别提取边缘信息和强度信息,再通过联合双边滤波器对成像模型中的散射函数进行估计,获取精细化的结果;定义远景区域缩小搜索范围,统计该区域内的灰度直方图计算环境光。仿真结果表明,该算法可有效提升能见度,增强图像的细节和颜色,得到相对较优的视觉效果。
Aiming at the problem of image degradation in hazy days,an efficient sharpening algorithm was proposed.The edge information and intensity information were extracted by using minimum value operation and morphological operation respectively,and then the scattering function in the imaging model was estimated by joint bilateral filter to obtain the refined results.By defining a distant view area to narrow the search scope,and the atmospheric light was calculated with the help of counting gray histogram.Simulation results show that the algorithm can effectively improve the visibility,detail and color of the image,and get a better visual effect.
作者
何惜琴
HE Xiqin(College of Electronic and Electrical Engineering,Minnan University of Science and Technology,Shishi 362700,China)
出处
《成都工业学院学报》
2022年第1期33-35,97,共4页
Journal of Chengdu Technological University
基金
福建省教育厅中青年教师教育科研项目(JAT190888)。
关键词
图像清晰化
图像去雾
图像复原
成像模型
image clearness
image defogging
image restoration
imaging model
