EN基于简单线性迭代聚类优化的无人机图像去雾算法及其在风电场中的应用
Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm
- 发电技术 2020年41卷第6期 页码：608-616
- 作者机构：
1.中国电子科技集团公司第五十四研究所, 河北省 石家庄市 050081
2.海装驻邯郸地区军事代表室, 河北省 石家庄市 050081
3.中国电子科技集团公司航天信息应用技术重点实验室, 河北省 石家庄市 050081
- 作者简介：
[ "刘厦(1986), 男, 硕士, 工程师, 研究方向为无人机智能测控, ykbrjslj@sina.cn" ]
[ "孙哲(1983), 男, 工程师, 研究方向为计算机视觉, power61104@163.com" ]
仇梓峰(1993), 男, 硕士, 工程师, 研究方向为基于无人机的图像处理, 本文通信作者, qzf93@qq.com
[ "胡炎(1991), 男, 硕士, 工程师, 研究方向为模式识别、健康管理及机器学习, huyantju@126.com" ]
- 基金信息：国家重点研发计划项目(2017YFB0503003)
DOI：10.12096/j.2096-4528.pgt.20006
中图分类号： TK83;TP391.41收稿：2020-03-17，
纸质出版：2020-12-31
- 稿件说明：
移动端阅览
刘厦, 孙哲, 仇梓峰, 等. 基于简单线性迭代聚类优化的无人机图像去雾算法及其在风电场中的应用[J]. 发电技术, 2020,41(6):608-616.
Sha LIU, Zhe SUN, Zifeng QIU, et al. Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm[J]. Power Generation Technology, 2020, 41(6): 608-616.
刘厦, 孙哲, 仇梓峰, 等. 基于简单线性迭代聚类优化的无人机图像去雾算法及其在风电场中的应用[J]. 发电技术, 2020,41(6):608-616. DOI： 10.12096/j.2096-4528.pgt.20006.
Sha LIU, Zhe SUN, Zifeng QIU, et al. Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm[J]. Power Generation Technology, 2020, 41(6): 608-616. DOI： 10.12096/j.2096-4528.pgt.20006.
摘要
针对电力巡检过程中无人机（unmanned aerial vehicle，UAV）载荷因受雾气颗粒影响而导致UAV图像不清晰的问题，提出一种基于简单线性迭代聚类（simple linear iterative clustering，SLIC）优化的UAV图像去雾算法。通过雾天成像物理模型、暗通道先验定律、同质滤波与SLIC算法，改善电力巡检图像中白色区域及不均匀光照的影响，提升UAV图像去雾处理的效率，并对大气光强度参数进行自适应计算，以防止去雾过程中复原失真。实验结果表明提出的算法可有效恢复电力巡检图像的原始细节，并通过主观视觉评估及融合多种客观评价指标的对比，说明该算法相对于传统算法的优越性。
Abstract
In order to solve the problem that the unmanned aerial vehicle (UAV) image is not clear due to the influence of fog particles
a UAV image dehazing algorithm based on simple linear iterative clustering (SLIC) optimization was proposed. Through the physical model of fog imaging
the prior law of dark channel
homogeneous filtering and SLIC algorithm
the influence of white area and uneven light in power inspection image was improved
the efficiency of UAV image dehazing was improved
and the adaptive calculation of atmospheric light intensity parameters was carried out to prevent the distortion in the dehazing process. The experimental results show that the algorithm can effectively restore the original details of the power inspection image. Through the comparison of subjective visual evaluation and fusion of a variety of objective evaluation indexes
it shows the superiority of the algorithm compared with the traditional algorithms.
关键词
Keywords
references
宋慧娟.基于混合现实的人工智能在电力巡检中的应用[J].电网与清洁能源, 2020, 36(2):75-79.
SONG H J.Application of the artificial intelligence based on mixed reality in power patrol inspection service[J].Power System and Clean Energy, 2020, 36(2):75-79.
孙旭日, 李延真, 彭博, 等.基于生成对抗网络和深度残差神经网络的变电站异物检测[J].电网与清洁能源, 2020, 36(9):68-75.
SUN X R, LI Y Z, PENG B, et al.Substation foreign object detection based on generative adversarial network and deep residual neural network[J].Power System and Clean Energy, 2020, 36(9):68-75.
杨东升, 王道浩, 周博文, 等.泛在电力物联网的关键技术与应用前景[J].发电技术, 2019, 40(2):107-114.
YANG D S, WANG D H, ZHOU B W, et al.Key technologies and application prospects of ubiquitous power internet of things[J].Power Generation Technology, 2019, 40(2):107-114.
彭福先, 张玮, 祝晓军, 等.基于激光点云精确定位的输电线路无人机自主巡检系统研究[J].智慧电力, 2019, 47(7):117-122.
PENG F X, ZHANG W, ZHU X J, et al.Autonomous patrol and inspection system of unmanned aerial vehicle for electric transmission lines based on precise positioning of laser point cloud[J].Smart Power, 2019, 47(7):117-122.
仇梓峰, 王爽心, 李蒙.基于无人机图像的风力发电机叶片缺陷识别[J].发电技术, 2018, 39(3):277-285.
QIU Z F, WANG S X, LI M.Defect detection of wind turbine blade based on unmanned aerial vehicle-taken images[J].Power Generation Technology, 2018, 39(3):277-285.
毛天奇, 王传策, 李云, 等.基于SGC算法的复杂背景无人机巡检图像输电线提取方法[J].智慧电力, 2018, 46(12):105-111.
MAO T Q, WANG C C, LI Y, et al.Transmission line extraction method based on SGC stereo matching algorithm for UAV inspection image under complex background[J].Smart Power, 2018, 46(12):105-111.
王丹, 李建岐, 廖斌.基于优化去雾算法的配网开关状态视频识别技术研究[J].电力信息与通信技术, 2017, 15(10):31-37.
WANG D, LI J Q, LIAO B.Research on video recognition technology of distribution switch based on optimized defogging algorithm[J].Electric Power Information and Communication Technology, 2017, 15(10):31-37.
禹晶, 徐东彬, 廖庆敏.图像去雾技术研究进展[J].中国图象图形学报, 2011, 16(9):1561-1576.
YU J, XU D B, LIAO Q M.Image defogging:a survey[J].Journal of Image and Graphics, 2011, 16(9):1561-1576.
KIM J Y, KIM L S, HWANG S H.An advanced contrast enhancement using partially overlapped sub-block histogram equalization[J].IEEE Transactions on Circuits and Systems for Video Technology, 2001, 11(4):475-484.
XIE C H, QIAO W W, ZHANG X X, et al.Single image dehazing algorithm using wavelet decomposition and fast kernel regression model[J].Journal of Electronic Imaging, 2016, 25(4):43-58.
肖胜笔, 李燕.具有颜色保真性的快速多尺度Retinex去雾算法[J].计算机工程与应用, 2015, 51(6):176-180.
XIAO S B, LI Y.Fast multiscale Retinex algorithm of image haze removal with color fidelity[J].Computer Engineering and Applications, 2015, 51(6):176-180.
GAO Y K, CHEN H Y, LI H B, et al.Single image dehazing using local linear fusion[J].IET Image Processing, 2018, 12(5):637-643.
FANG S, XIA X S, HUO X, et al.Image dehazing using polarization effects of objects and airlight[J].Optics Express, 2014, 22(16):195-211.
KOPF J, NEUBERT B, CHEN B, et al.Deep photo:model-based photograph enhancement and viewing[J].ACM Transactions on Graphics, 2008, 27(5):116-125.
NARASIMHAN S G, NAYAR S K.Contrast restoration of weather degraded images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(6):711-724.
FATTAL R.Single image dehazing[J].ACM Transactions on Graphics, 2008, 27(3):1-13.
MENG G, WANG Y, DUAN J, et al.Efficient image dehazing with boundary constraint and contextual regularization[C]//2013 IEEE International Conference on Computer Vision.IEEE, 2014: 1-13.
HE K M, SUN J, TANG X O, et al.Single image haze removal using dark channel prior[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12):2341-2353.
PEI S C, LEE T Y.Nighttime haze removal using color transfer pre-processing and dark channel prior[C]//201219th IEEE International Conference on Image Processing (ICIP).IEEE, 2012: 3-15.
FENG C, ZHUO S, ZHANG X, et al.Near-infrared guided color image dehazing[C]//2013 IEEE International Conference on Image Processing.IEEE, 2013: 1-13.
BUI T M, TRAN H N, KIM W, et al.Segmenting dark channel prior in single image dehazing[J].Electronics Letters, 2014, 50(7):516-518.
YUE B X, LIU K L, WANG Z Y, et al.Accelerated haze removal for a single image by dark channel prior[J].Frontiers of Information Technology&Electronic Engineering, 2019, 20(8):1109-1118.
CONG J, WEI B, YIN Y, et al.Performance evaluation of simple linear iterative clustering algorithm on medical image processing[J].Bio-medical Materials and Engineering, 2014, 24(6):3231-3238.
SHAHAMAT H, POUYAN A A.Face recognition under large illumination variations using homomorphic filtering in spatial domain[J].Journal of Visual Communication and Image Representation, 2014, 25(5):970-977.
QU J, LI Y, DONG W.Fusion of hyperspectral and panchromatic images using an average filter and a guided filter[J].Journal of Visual Communication&Image Representation, 2018:52-63.
0
浏览量
0
下载量
0
CSCD
- 网络PDF下载
- Meta-XML下载
- BibTeX下载
- Endnote下载
- RefMan 下载
- NoteExpress下载
- NoteFirst下载
关联资源
相关文章
相关作者
相关机构
AI问答- 技术支持由北京北大方正电子有限公司提供 京ICP备09064830号-19
京公网安备11010802024621 - 本系统建议在Chrome、 IE9+ 以上版本浏览器阅读本站内容，360浏览器请切换至极速模式
- Cookies帮助我们提供服务并提供个性化体验。使用本网站，即表示您同意我们使用Cookies