基于暗通道先验改进的实时去雾算法
首发时间:2018-07-05
摘要:基于暗通道先验理论的去雾算法有着良好的去雾效果,是诸多雾霾图像恢复算法的典型,但其在车载等方面的实际运用中拥有诸多缺陷。为了减小由于算法本身造成的白场现象和色调失衡等问题,本文提出一种针对此算法的优化和改进。该算法首先改良了透射率曲线,使得图像亮度较大的区域恢复效果趋于平滑;再通过HSV颜色空间对色度的分割来替换原图的色彩比例,以此矫正失衡的亮度与色度;改进后的算法还利用了各种快速算法简化了计算,从而实现了实时去雾。在Open CV的软件平台下,得到了良好的实验结果,证明了算法的有效性。
For information in English, please click here
Real-time defogging algorithm based on dark channel priori improvement
Abstract:The defogging algorithm based on the dark channel prior theory has a good defogging effect and is typical of many haze image restoration algorithms, but it has many defects in the practical application of vehicle-mounted and other aspects. In order to reduce the white field phenomenon and tonal imbalance caused by the algorithm itself, this paper proposes an optimization and improvement for this algorithm. The algorithm firstly improves the transmittance curve, which makes the recovery effect of the region with larger brightness of the image tends to be smooth. Then, the color ratio of the original image is replaced by the HSV color space to rectify the unbalanced brightness and chromaticity. The improved algorithm also utilises a variety of fast algorithms to simplify calculations and achieve real-time defogging. Under the Open CV software platform, good experimental results are obtained, which proves the effectiveness of the algorithm
Keywords: Image recovery video defogging dark color prior transmission color correction
基金:
引用
No.****
动态公开评议
共计0人参与
勘误表
基于暗通道先验改进的实时去雾算法
评论
全部评论0/1000