摘要
为解决传统基于暗原色先验的去雾算法在景物边界处出现的白边现象,以及在天空、白云等明亮区域出现的颜色失真的问题,提出一种基于色彩空间的快速去雾算法.首先把暗原色先验值求解中对邻域求最小值操作改为求中值操作;然后根据RGB色彩空间中像素颜色深度变化正好与场景深度变化相对应的关系,引入像素最大值与最小值之差的加权来调整暗原色先验值;再根据阈值来区分是否是明亮区域,修改明亮区域透射率估计的不足;最后在HIS色彩空间复原强度分量和饱和度值,并用直方图拉伸增强强度分量.文中算法无需图像后期修补,能自适应地修改暗原色先验值,实验结果表明了该算法的可行性和有效性.
The traditional image dehazing algorithm based on dark channel prior has some shortages such as the white border in the scene, and color distortion appeared in the bright areas of sky and cloud. In order to solve these problems, this paper proposes a fast algorithm based on color space. First, finding the minimum value in the neighbourhood is replaced by computing the mean value in solving dark channel prior. Then according to the relationship between pixel color depth in RGB space and real scene depth information, the dark colors priori is adjusted by using the weighted difference between maximum and minimum values. The threshold value is used to distinguish whether it is a bright area, and then underestimated transmittance is modified. The intensity component and saturation value are recovered in HIS color space. Finally, the histogram stretching is employed to enhance the intensity component. This method does not need image post repairing and can adaptively change the dark channel prior values. The experimental results demonstrates the effectiveness and feasibility of the proposed algorithm.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2015年第8期1506-1511,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(11172138)
福建省自然科学基金(2012J05008)
