基于Otsu和FMM方法的风洞试验图像修复

doi:10.7527/S1000-6893.2019.23293

流体力学与飞行力学

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

基于Otsu和FMM方法的风洞试验图像修复

江涛, 李强, 陈苏宇, 常雨, 张扣立

中国空气动力研究与发展中心超高速空气动力研究所, 绵阳 621000

收稿日期:2019-07-17 修回日期:2019-08-13 出版日期:2020-02-15 发布日期:2019-09-23
通讯作者: 张扣立 E-mail:zhangkouli@cardc.cn
基金资助:
国家重点研发计划（2016YFA0401201）

Image inpainting of wind tunnel test based on Otsu method and FMM

JIANG Tao, LI Qiang, CHEN Suyu, CHANG Yu, ZHANG Kouli

Hypervelocity Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China

Received:2019-07-17 Revised:2019-08-13 Online:2020-02-15 Published:2019-09-23
Supported by:
National Key Research and Development Program of China (2016YFA0401201)

摘要/Abstract

摘要： 各种光学测试技术在风洞试验中应用越来越广泛，图像中的破损或无关信息均会影响数据的处理和分析。以存在缺陷的风洞纹影图像为例，对数字图像修复技术进行了研究。根据缺陷离散分布、大小及形状各异，核心区域的灰度值较低以及边缘处灰度梯度变化较大等特点，将图像修复流程设计为确定待处理区域、缺陷识别和缺陷修复等3个步骤。前2个步骤使用Otsu算法进行图像的分割处理，然后使用快速行进方法（FMM）完成缺陷修复。经处理，纹影图像的缺陷被自动识别，并得到了减少或削弱，而且修复的信息客观合理。该方法可推广至其他光学测试技术的图像修复。

关键词: 图像修复, Otsu算法, 快速行进方法, 纹影, 光学, 风洞试验

Abstract: Many kinds of optics test technologies have been applied broadly in wind tunnel test, but the breakages and irrelevant information of images could affect data processing and analysis. Taking schlierern images with defects as an example, the image inpainting technology is studied. According to the characteristics of the image defects such as discrete, variable in shape and size, low gray levels of core regions and large gray gradients on the edges of defects, the image inpainting workflow is divided into pending regions determination, defects identification, and defects inpainting. The Otsu method is used to segment images in Step 1 and Step 2, and the Fast Marching Method (FMM) is applied to inpaint the defects in Step 3. After image inpainting, the defects of schlieren images are automatically identified and reduced or weakened, and the inpainting information is objective and reasonable. This image inpainting method could be extended to other optics test technologies in wind tunnel test.

Key words: image inpainting, Otsu method, fast marching method, schlieren, optics, wind tunnel test

中图分类号:

江涛, 李强, 陈苏宇, 常雨, 张扣立. 基于Otsu和FMM方法的风洞试验图像修复[J]. 航空学报, 2020, 41(2): 123293-123293.

JIANG Tao, LI Qiang, CHEN Suyu, CHANG Yu, ZHANG Kouli. Image inpainting of wind tunnel test based on Otsu method and FMM[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(2): 123293-123293.

参考文献 27

[1]	杨祖清. 流动显示技术[M]. 北京:国防工业出版社, 2002:93-276. YANG Z Q. Flow visualization[M]. Beijing:National Defense Industry Press, 2002:93-276(in Chinese).
[2]	李桂春. 气动光学[M]. 北京:国防工业出版社, 2002:347-489. LI G C. Aero-optics[M]. Beijing:National Defense Industry Press, 2002:347-489(in Chinese).
[3]	李强, 江涛, 陈苏宇, 等. 激波风洞边界层转捩测量技术及应用[J]. 航空学报, 2019, 40(8):122740. LI Q, JIANG T, CHEN S Y, et al. Measurement technology and measuring of boundary layer transition in shock tunnel[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(8):122740(in Chinese).
[4]	战培国, 曾慧, 钟萍, 等. 2017年国外风洞试验发展动态综述[J]. 飞航导弹, 2018(8):16-48. ZHAN P G, ZENG H, ZHONG P, et al. Review of the development of foreign wind tunnel tests in 2017[J]. Aerodynamic Missile Journal, 2018(8):16-48(in Chinese).
[5]	GABRIELE B, GUILLAUME G, TAMAS R, et al. Optical characterization of boundary layer transition[C]//17th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2014.
[6]	张扣立, 周嘉穗, 孔荣宗, 等. CARDC激波风洞TSP技术研究进展[J]. 空气动力学学报, 2016, 34(6):738-743. ZHANG K L, ZHOU J S, KONG R Z, et al. Development of TSP technique in shock tunnel of CARDC[J]. Acta Aerodynamica Sinica, 2016, 34(6):738-743(in Chinese).
[7]	韩曙光, 贾广森, 文帅, 等. 磷光热图技术在常规高超声速风洞热环境实验中的应用[J]. 气体物理, 2017, 2(4):56-63. HAN S G, JIA G S, WEN S, et al. Heat transfer measurement using a quantitative phosphor thermography system in blowdown hypersonic facility[J]. Physics of Gases, 2017, 2(4):56-63(in Chinese).
[8]	刘祥. 双组份压敏漆试验技术测量不确定度研究[D]. 绵阳:中国空气动力研究与发展中心, 2016. LIU X. Investigation of pressure uncertainty for two-component pressure sensitive paint[D]. Mianyang:China Aerodynamics Research and Development Center, 2016(in Chinese).
[9]	BERTALMIO M,SAPIRO G, CASELLES V, et al. Image inpainting[C]//Proceedings SIGGRAPH 2000, Computer Graphics Proceedings, Annual Conference Series, 2000:417-424.
[10]	GUILLEMOT C, LE MEUR O. Image inpainting:Overview and recent advances[J]. IEEE Signal Processing Magazine, 2014, 31(1):127-144.
[11]	张红英. 数字图像修复技术的研究与应用[D]. 成都:电子科技大学, 2006:1-32. ZHANG H Y. Research and application digital image inpainting[D]. Chengdu:University of Electronic and Technology of China, 2006:1-32(in Chinese).
[12]	张丽莹. 数字图像修复算法研究[D]. 天津:天津大学, 2015:1-18. ZHANG L Y. The study of digital image completion algorithms[D]. Tianjin:Tianjin University, 2015:1-18(in Chinese).
[13]	SHIH T K, CHANG R C, LU L C, et al. Multi-layer inpainting on Chinese artwork restoration applications[C]//IEEE International Conference on Multimedia and Expo. Piscataway, NJ:IEEE Press, 2004.
[14]	焦莉娟, 王文剑, 李秉婧, 等. 改进的块匹配五台山壁画修复算法[J]. 计算机辅助设计与图形学学报, 2019, 31(1):118-125. JIAO L J, WANG W J, LI B J, et al. Wutai Mountain mural inpainting based on improved block matching algorithm[J]. Journal of Computer-Aided Design & Computer Graphics, 2019, 31(1):118-125(in Chinese).
[15]	罗希平, 田捷, 诸葛婴, 等. 图像分割方法综述[J]. 模式识别与人工智能, 1999, 12(3):300-312. LUO X P, TIAN J, ZHUGE Y, et al. A survey on image segmentation techniques[J]. Pattern Recognition and Artificial Intelligence, 1999, 12(3):300-312(in Chinese).
[16]	林开颜, 吴军辉, 徐立鸿. 彩色图像分割方法综述[J]. 中国图象图形学报, 2005, 10(1):1-10. LIN K Y, WU J H, XU L H. A survey on color image segmentation techniques[J]. Journal of Image and Graphics, 2005, 10(1):1-10(in Chinese).
[17]	韩思奇, 王蕾. 图像分割的阈值法综述[J]. 系统工程与电子技术, 2002, 24(6):91-94. HAN S Q, WANG L. A survey of thresholding methods for image segmentation[J]. Systems Engineering and Electronics, 2002, 24(6):91-94(in Chinese).
[18]	SEZGIN M, SANKUR B. Survey over image thresholding techniques and quantitative performance evaluation[J]. Journal of Electronic Imaging, 2004, 13(1):146-165.
[19]	NOBUYUKI O. A threshold selection method from gray-level histogram[J]. IEEE Transactions on Systems, Man and Cybernetics, 1979, 9(1):62-66.
[20]	付忠良. 图像阈值选取方法——Otsu方法的推广[J]. 计算机应用, 2000, 20(5):37-39. FU Z L. Methods of selecting image threshold-Extension of Otsu method[J]. Computer Applications, 2000, 20(5):37-39(in Chinese).
[21]	刘艳, 赵英良. Otsu多阈值快速求解算法[J]. 计算机应用, 2011, 31(12):3363-3365. LIU Y, ZHAO Y L. Quick approach of multi-threshold Otsu method for image segmentation[J]. Journal of Computer Applications, 2011, 31(12):3363-3365(in Chinese).
[22]	申铉京, 刘翔, 陈海鹏. 基于多阈值Otsu准则的阈值分割快速计算[J]. 电子与信息学报, 2017, 39(1):144-149. SHEN X J, LIU X, CHEN H P. Fast computation of threshold based on multi-threshold Otsu criterion[J]. Journal of Electronics & Information Technology, 2017, 39(1):144-149(in Chinese).
[23]	周迪, 夏哲雷. 一种改进的Otsu阈值分割算法[J]. 中国计量大学学报, 2016, 23(1):319-323. ZHOU D, XIA Z L. An improved Otsu threshold segmentation algorithm[J]. Journal of China University of Metrology, 2016, 23(1):319-323(in Chinese).
[24]	李开宇, 孙玉刚. 引入连续性强度和置信度因子的快速图像修复[J]. 中国图象图形学报, 2012, 17(4):465-470. LI K Y, SUN Y G. Fast image inpainting algorithm introducing continuous strength and confidence factor[J]. Journal of Image and Graphics, 2012, 17(4):465-470(in Chinese).
[25]	闵溪青, 黄杰. 简化的快速图像修复方法[J]. 计算机应用, 2017, 37(S1):169-172. MIN X Q, HUANG J. Simplified fast image inpainting method[J]. Journal of Computer Applications, 2017, 37(S1):169-172(in Chinese).
[26]	SETHIAN J A. A fast marching level set method for monotonically advancing fronts[J]. National Academy of Sciences, 1996, 93(4):1591-1595.
[27]	TELEA A. An image technique based on the fast matching method[J]. Journals of Graphics Tools, 2004, 9(1):23-34.

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于Otsu和FMM方法的风洞试验图像修复

Image inpainting of wind tunnel test based on Otsu method and FMM

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 27

相关文章 15

编辑推荐

Metrics

本文评价

[1]	左富昌, 梅志武, 邓楼楼, 周昊, 贝晓敏, 黎月明. 脉冲星角位置强度关联测量聚焦光学系统[J]. 航空学报, 2023, 44(3): 527124-527124.
[2]	李连升, 梅志武, 谢军, 姜坤, 石永强, 曹振, 左富昌. X射线聚焦光学在脉冲星探测领域的应用[J]. 航空学报, 2023, 44(3): 528286-528286.
[3]	刘中臣, 钱战森, 李雪飞, 冷岩, 郭大鹏. 发动机喷管羽流对近场声爆特性影响的风洞试验技术[J]. 航空学报, 2023, 44(2): 626952-626952.
[4]	徐善劼, 吕宏强, 刘中臣, 冷岩, 刘学军. 基于概率模型的声爆试验数据分析[J]. 航空学报, 2023, 44(2): 626269-626269.
[5]	束珺, 徐东光, 韩志熔, 李斯, 黄雄. 结冰风洞过冷大水滴试验中混合翼设计[J]. 航空学报, 2023, 44(1): 627182-627182.
[6]	罗凯, 王永海, 汪球, 栗继伟, 李峥, 聂春生, 李铮. 高焓风洞中等离子体激励流动控制试验[J]. 航空学报, 2022, 43(S2): 89-96.
[7]	杜海, 杨乐杰, 李铮, 徐悦, 孙京阳, 王宇航. 多级环量控制技术增升机理及能效分析[J]. 航空学报, 2022, 43(S2): 54-66.
[8]	刘传振, 孟旭飞, 刘荣健, 白鹏. 双后掠乘波体高超声速试验与数值分析[J]. 航空学报, 2022, 43(9): 126015-126015.
[9]	刘俊, 罗新福, 王显圣. 前缘形状对空腔模型气动特性影响试验[J]. 航空学报, 2022, 43(7): 125235-125235.
[10]	侯英昱, 李齐, 季辰, 刘子强. 超声速低频大抖振气动弹性载荷试验[J]. 航空学报, 2022, 43(3): 626454-626454.
[11]	张桢锴, 贾思嘉, 宋晨, 杨超. 柔性变弯度后缘机翼的风洞试验模型优化设计[J]. 航空学报, 2022, 43(3): 226071-226071.
[12]	曾开春, 寇西平, 杨兴华, 余立, 查俊. 跨声速风洞试验模型主动减振结构优化设计[J]. 航空学报, 2022, 43(2): 224944-224944.
[13]	衣秉立, 刘博宇, 王争取, 张铁军, 鲁丹, 赵彦. 1.2 m高速风洞双天平支撑试验技术[J]. 航空学报, 2022, 43(11): 526794-526794.
[14]	姜有旭, 李杰, 杨钊. 某层流机翼验证机风洞试验数据修正方法[J]. 航空学报, 2022, 43(11): 526814-526814.
[15]	王猛, 李玉军, 赵荣奂, 衷洪杰. 基于在线加热涂层的宽速域转捩探测技术[J]. 航空学报, 2022, 43(11): 526820-526820.