Please wait a minute...
img

官方微信

遥感技术与应用  2015, Vol. 30 Issue (1): 140-147    DOI: 10.11873/j.issn.1004-0323.2015.1.0140
图像与数据处理     
基于高斯差分模型的雪地扰动痕迹遥感识别
刘吉磊1,2,李强子1,杜鑫1
(1.中国科学院遥感与数字地球研究所,北京100101;2.中国科学院大学,北京100049)
Recognition of Activity Tracks in the Snow with Remote Sensing based on Difference of Gaussian Filter
Liu Jilei1,2,Li Qiangzi1,Du Xin1
(1.Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences,Beijing 100101,China;
2.University of Chinese Academy of Sciences,Beijing 100049,China)
 全文: PDF(3433 KB)  
摘要:

雪面上人或动物的活动信息涉及冬季动物迁移追踪、人员活动轨迹检测、安全防卫等各领域应用,利用遥感技术监测人或动物的活动痕迹可以及时掌握动物的迁移情况、江上人员活动范围等信息,进而可为相应的管理决策提供依据。利用高分辨率遥感技术,通过图像滤波等增强处理,可以识别冰雪覆盖区域经人或动物活动后产生的微弱线状扰动痕迹,为后续分析提供帮助。提出了利用高斯差分滤波器(DoG)进行冬季冰雪覆盖区域扰动痕迹识别的监测方法。通过对吉林省龙井市结冰江面上活动痕迹的实验表明,当σ取1.5时,DoG带通滤波频率与人员过江痕迹频率一致,对痕迹增强效果最明显,此时的滤波器为最佳滤波器,痕迹总体提取精度达到83.67%,优于传统的Laplacian算子、Sobel算子和Prewitt算子滤波方法。说明通过DoG滤波器处理,能够有效地突出雪面上人或动物的活动痕迹,可为进一步识别

关键词: 高分辨率遥感高斯差分滤波器雪地痕迹目标识别    
Abstract:

Human or animal activity information on snow relates to applications in various fields animal tracking such as,in winter,animal migration tracking,public safety and defense,etc.Remote sensing technologies can play key roles in monitoring the tracks of human or animal activity traces through image enhancement,e.g.filter techniques with very high spatial resolution images,especially linear disturbance traces from human or animal activities in snow\|covered area,and grasp the animal migration,human activities on the frozen river and other information timely to further assist in decision\|making.In this paper the principle and characteristics of the Difference of Gaussian filter(DoG) were proposed to identify linear disturbance traces in the snow,and experiments showed that the accuracy of traces extraction reached 83.67% with an adaptive filter(σ=1.5).The results were more reliable and effective than that from laplacian,sobel and prewitt operators.DoG filter is more suitable for human activity traces identification on the frozen river,and will play a key role in further services for recognizing human or animal activity type,trace route,as well as security patrols of relevant departments.


Key words: High resolution    Remote sensing    Difference of Gaussian Filter    Snow tracks    Target recognition
收稿日期: 2013-10-27 出版日期: 2015-03-11
:  TP 751.1  
基金资助:

高分辨率对地观测系统重大专项(01-Y30A03-9001-12/13)。

通讯作者: 李强子(1970-),男,河南新安人,博士,研究员,主要从事农业遥感、高分辨率遥感信息分析等方面的研究。Email:liqz@radi.ac.cn。    
作者简介: 刘吉磊(1989-),男,山东菏泽人,硕士研究生,主要从事高分辨率遥感目标识别与应用方面的研究。Email:Liujl@radi.ac.cn。
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
刘吉磊
李强子
杜鑫

引用本文:

刘吉磊,李强子,杜鑫. 基于高斯差分模型的雪地扰动痕迹遥感识别[J]. 遥感技术与应用, 2015, 30(1): 140-147.

Liu Jilei,Li Qiangzi,Du Xin. Recognition of Activity Tracks in the Snow with Remote Sensing based on Difference of Gaussian Filter. Remote Sensing Technology and Application, 2015, 30(1): 140-147.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.1.0140        http://www.rsta.ac.cn/CN/Y2015/V30/I1/140

[1]Sun Zhiqun.The Inversion of Snow Cover and Snow Surface Temperature based on Mutisource Remote Sensing Data [D].Urumqi:Xinjiang University,2012.[孙志群.基于多源遥感影像的雪盖及雪表面温度反演[D].乌鲁木齐:新疆大学,2012.]

[2]Becker E F,Spindler M A,Osborne T O.A Population Estimator based on Network Sampling of Tracks in the Snow[J].Journal of Wildlife Management,1998,62(3):968-977.

[3]D’Eon R G.Using Snow-track Surveys to Determine Deer Winter Distribution and Habitat[J].Wild Soc Bull,2001,29:879-887.

[4]Li Xiaohong.A Study of Edge Detection Algorithm based on LoG Filter[J].Computer Application and Software,2005,22(5):107-108.[李小红.基于LoG滤波器的图像边缘检测算法的研究[J].计算机应用与软件,2005,22(5):107-108.]

[5]Jia Yunde.Machine Version[M].Beijing:Science Press,2000.[贾云得.机器视觉[M].北京:科学出版社,2000.]

[6]Rafael C G,Richard E W.Digital Image Processing[M].Beijing:Publishing House of Electronics Industry,2011.

[7]Marr D,Hildreth E.Theory of Edge Detection[J].Proceedings of the Royal Society of London,1980,207:187-217.

[8]Marr D.Vision:A Computational Investigation into the Human Representation and Processing of Visual Information[M].San Francisco:The MIT Press,2010.

[9]Lathi B P.Signal Processing and Linear Systems[M].Oxford:Oxford University Press,2009.

[10]Xie Shaohui,Wu Lide.Some Research about Operator[J].Acta Automatica Sinica,1990,16(3):193-202.[谢绍辉,吴立德.关于算子的一些研究[J].自动化学报,1990,16(3):193-202.]

[11]Luo Xiaohui,Li Jianwei.DOG Mode-based Algorithm of Line Detection[J].Journal of Computer Aided Design and Computer Graphics,2003,15(4):425-431.[罗晓晖,李见为.基于DoG模型的线条检测算法[J].计算机辅助设计与图形学报,2003,15(4):425-431.]

[12]Xu Jingbo.Study on Approximation Theory and Application of Gaussian Filter[D].Harbin:Harbin Institute of Technology Press,2007.[许景波.高斯滤波器逼近理论与应用研究[D].哈尔滨:哈尔滨工业大学,2007.]

[13]Rodieck R W,Stone J.Analysis of Receptive Fields of Cat retinal Ganglion Cells[J].Journal of Neurophysiology,1965,28(5):832-49.

[14]Philip B,Bhargav M,Nagachetan M,et.al.Approximate Bandpass and Frequency Response Models of the Difference of Gaussian Filter[J].Optics Communications,2010,283(24):4942-4948.

[15]Liu Bin,Yan Jingqi,Shi Pengfei.A License Plate Location Method based on the DoG and AdaBoost Algorithm[J].CAAI Transactions on Intelligent Systems,2010,5(6):471-475.[刘彬,严京旗,施鹏飞.高斯差分的AdaBoost车牌定位方法[J].智能系统学报,2010,5(6):471-475.]

[16]You Lei,Yang Dan,Zhang Xiaohong.A New Stereo Matching Algorithm based on Difference of Gaussian[J].Journal of Chongqing Institute of Technology(Natural Science),2009,23(1):122-160.[游磊,杨丹,张小洪.一种新的基于DoG的立体匹配算法[J].重庆工学院学报,2009,23(1):122-160.]

[17]Wang Zhaozhong,Zhou Fugen.Nonuniform Illumination Correction based on Difference of Gaussian Filter[J].Infrared and Laser Engineering,2000,29(6):64-67.[王兆仲,周付根.基于高斯差分滤波器的图像光场矫正[J].红外与激光工程,2000,29(6):64-67.]

[1] 王卷乐, 程凯, 边玲玲, 韩雪华, 王明明. 面向SDGs和美丽中国评价的地球大数据集成框架与关键技术[J]. 遥感技术与应用, 2018, 33(5): 775-783.
[2] 王恺宁,王修信,黄凤荣,罗涟玲. 喀斯特城市地表温度遥感反演算法比较[J]. 遥感技术与应用, 2018, 33(5): 803-810.
[3] 张晓峰,吕晓琪,张信雪,张继凯,王月明,谷宇,樊宇. 多时刻海色遥感数据融合及其可视化[J]. 遥感技术与应用, 2018, 33(5): 873-880.
[4] 谢旭,陈芸芝. 基于PSO-RBF神经网络模型反演闽江下游水体悬浮物浓度[J]. 遥感技术与应用, 2018, 33(5): 900-907.
[5] 迟文峰,匡文慧,贾静,刘正佳. 京津风沙源治理工程区LUCC及土壤风蚀强度动态遥感监测研究[J]. 遥感技术与应用, 2018, 33(5): 965-974.
[6] 胡云锋,商令杰,张千力,王召海. 基于GEE平台的1990年以来北京市土地变化格局及驱动机制分析[J]. 遥感技术与应用, 2018, 33(4): 573-583.
[7] 李晨伟,张瑞丝,张竹桐,曾敏 . 基于多源遥感数据的构造解译与分析—以西藏察隅吉太曲流域为例[J]. 遥感技术与应用, 2018, 33(4): 657-665.
[8] 李生生,王广军,梁四海,彭红明,董高峰,罗银飞. 基于Landsat-8 OLI数据的青海湖水体边界自动提取[J]. 遥感技术与应用, 2018, 33(4): 666-675.
[9] 廖凯涛,齐述华,王成,王点. 结合GLAS和TM卫星数据的江西省森林高度和生物量制图[J]. 遥感技术与应用, 2018, 33(4): 713-720.
[10] 张震,刘时银,魏俊锋,蒋宗立. 1974~2012年珠穆朗玛峰地区冰川物质平衡遥感监测研究[J]. 遥感技术与应用, 2018, 33(4): 731-740.
[11] 王琳,徐涵秋,李胜. 重钢重工业区迁移对区域生态的影响研究[J]. 遥感技术与应用, 2018, 33(3): 387-397.
[12] 任浙豪,周坚华. 增大特征空间复杂度的方法——以城镇下垫面遥感分类为[J]. 遥感技术与应用, 2018, 33(3): 408-417.
[13] 王宝刚,晋锐,赵泽斌,亢健. 被动微波遥感在地表冻融监测中的应用研究进展[J]. 遥感技术与应用, 2018, 33(2): 193-201.
[14] 秦振涛,杨茹,张靖,杨武年. 基于聚类结构自适应稀疏表示的高光谱遥感图像修复研究[J]. 遥感技术与应用, 2018, 33(2): 212-215.
[15] 郭宇柏,卓莉,陶海燕,曹晶晶,王芳. 基于空谱初始化的非负矩阵光谱混合像元盲分解[J]. 遥感技术与应用, 2018, 33(2): 216-226.