Image Dehazing Method of Transmission Line for Unmanned Aerial Vehicle Inspection Based on Densely Connection Pyramid Network
Image Dehazing Method of Transmission Line for Unmanned Aerial Vehicle Inspection Based on Densely Connection Pyramid Network
复制标题
基于密集连接金字塔网络的无人机巡检输电线路图像去雾方法
DOI：
10.1155/2020/8857271
复制
发表时间：
2020-10-08
影响因子：
--
通讯作者：
Wang, Xiaoyang
中科院分区：
文献类型：
--
作者：
Liu, Jun;Jia, Rong;Wang, Xiaoyang
摄像机图像的质量直接决定了输电线路设备缺陷识别的准确性。然而，雾霾等复杂的外部因素会严重影响飞机的图像质量。传统的图像去雾方法难以满足复杂环境下图像增强检测的需要。本文对雾霾环境下的图像增强技术进行了研究，提出了一种基于密集连接金字塔网络的输电线路图像去雾方法。该方法采用改进的金字塔网络计算透射率图，采用改进的U形网络计算大气光值。然后，将透射率图、大气光值和去雾图像进行联合优化，得到图像去雾模型。与传统的去模糊方法相比，本文提出的方法可以提高图像的亮度和对比度，增加图像的细节信息，生成更真实的去模糊图像。
The quality of the camera image directly determines the accuracy of the defect identification of the transmission line equipment. However, complex external factors such as haze can seriously affect the image quality of the aircraft. The traditional image dehazing methods are difficult to meet the needs of enhanced image inspection in complex environments. In this paper, the image enhancement technology in haze environment is studied, and an image dehazing method of transmission line based on densely connection pyramid network is proposed. The method uses an improved pyramid network for transmittance map calculation and uses an improved U-net network for atmospheric light value calculation. Then, the transmittance map, atmospheric light value, and dehazed image are jointly optimized to obtain image dehazing model. The method proposed in this paper can improve image brightness and contrast, increase image detail information, and can generate more realistic deblur images than traditional methods.