摘要
为解决现有去雾算法结果中存在的光晕现象、颜色失真等问题,提出一种基于边界邻域最大值滤波的图像去雾方法.首先通过边缘检测寻找图像边界被低估的暗原色值并对其进行边界邻域最大值滤波,以得到更为准确的透射率图来消除光晕现象;其次对暗原色图乘以一个尺度因子,扩大透射率的取值范围,提高去雾结果的对比度;最后设置两个亮度阈值以及一个平坦阈值,消除图像中高亮度物体的影响,获得更为准确的大气光值,使得去雾结果颜色保真度较高.仿真结果表明,与现有去雾算法相比,本文算法对含高亮度物体以及含细节信息的带雾图像,均可消除光晕现象,获得高对比度及高颜色保真度的去雾结果,同时也提高了算法的处理速度.
A fast image defogging algorithm based on edge-maximum filter was proposed to address halo effect and color distortion caused by the existing defogging methods.Firstly,an edge-maximum filter was used to recover the undervalued dark pixels obtained by edge detection,which was to receive an accurate transmission map and eliminate the halo effect.Then in order to gain a high contrast dehazing image,all the dark pixels were multiplied by a scaling factor to improve the dynamic ranges of the transmission.Finally,two brightness thresholds and one flat threshold were set to eliminate the influence of high light objects in the image and obtain a more accurate airlight,which keeps a high color fidelity in the dehazing image.The simulation results show that the proposed method,compared with other algorithms,could eliminate the halo effect and achieve the dehazing image with high contrast and high color fidelity,especially for the images containing high light objects or rich details.Meanwhile,the computational speed is also improved.
出处
《光子学报》
EI
CAS
CSCD
北大核心
2014年第11期108-113,共6页
Acta Photonica Sinica
基金
国家自然科学基金(61373180)
2014年西南交通大学博士研究生创新基金
中央高校基本科研业务费专项基金
