Volume 38 Issue 1
Jan.  2012
Turn off MathJax
Article Contents
Gu Duoyu, Guo Jiang, Li Shuxiao, et al. Resident region extraction using Gabor filter in aerial imagery[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(1): 106-110,122. (in Chinese)
Citation: Gu Duoyu, Guo Jiang, Li Shuxiao, et al. Resident region extraction using Gabor filter in aerial imagery[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(1): 106-110,122. (in Chinese)

Resident region extraction using Gabor filter in aerial imagery

  • Received Date: 06 Sep 2010
  • Publish Date: 30 Jan 2012
  • Automatic extraction of resident regions from medium and low revolution aerial images plays a crucial role in geographic information system(GIS) updating and unmanned aerial vehicle(UAV) navigation. The parameters of Gabor filter in detail were analyzed, and a fast resident region extraction algorithm based on Gabor filter was proposed. The method composed of four steps. Firstly, the texture features of input image were extracted using Gabor filter. And then the texture features were smoothed by the kernel density estimation method to get the confidence image. Subsequently, the confidence image was segmented by the basic global threshold algorithm to acquire candidate regions. Ultimately, the candidate regions were verified by the geometric structure information. The method has low computational complexity, and can run within 0.42s in average. The efficiency and accuracy of the proposed algorithm were demonstrated by the experimental results.

     

  • loading
  • [1] Jolly M P D,Gupta A.Color and texture fusion:application to aerial image segmentation and GIS updating[J].Image and Vision Computing,2000,18(10):823-832 [2] Unsalan C,Boyer K L.Classifying land development in high-resolution panchromatic satellite images using straight-line statistics[J].Geoscience and Remote Sensing,IEEE Transactions on,2004,42(4):907-919 [3] Lorette A,Descombes X,Zerubia J.Texture analysis through a Markovian modelling and fuzzy classification:application to urban area extraction from satellite images[J].International Journal of Computer Vision,2000,36(3):221-236 [4] 文贡坚,李德仁,叶芬.从卫星遥感全色图像中自动提取城市目标[J].武汉大学学报:信息科学版,2003,28(2):212-218Wen Gongjian,Li Deren,Ye Fen.Automatic extraction of urban area from satellite panchromatic remote sensing images[J].Journal of Wuhan University:Geomatics and Information Science,2003,28(2):212-218(in Chinese) [5] Zhong Ping,Wang Runsheng.Using combination of statistical models and multilevel structural information for detecting urban areas from a single gray-level image[J].Geoscience and Remote Sensing,IEEE Transactions on,2007,45(5):1469-1482 [6] Sirmacek B,Unsalan C.Urban area detection using local feature points and spatial voting[J].Geoscience and Remote Sensing Letters,IEEE,2010,7(1):146-150 [7] May S,Inglada J.Urban area detection and segmentation using OTB[C]//Geoscience and Remote Sensing Symposium,2009 IEEE International.Cape Town,South Africa:[s.n.],2009,4:928-931 [8] Wang Min.Influence of number of features on texture based residential area extraction from remotely sensed imagery[C]//Image and Signal Processing,2nd International Congress on.Tianjin:[s.n.],2009:1-4 [9] Pesaresi M,Gerhardinger A,Kayitakire F.A robust built-up area presence index by anisotropic rotation-invariant textural measure[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2008,1(3):180-192 [10] Movellan J. Tutorial on gabor filters[R/OL].(1996)http://mplab.ucsd.edu/wordpress/tutorials/gabor.pdf [11] Viola P,Jones M J.Robust real-time face detection [J].Int J Comput Vis,2004,57(2):137-154 [12] Gonzalez Raphael,Woods Richard E.Digital image processing,second edition [M].Beijing:Publishing House of Electronics Industry,2008:598-600 [13] Lipton A J,Fujiyoshi H,Patil R S.Moving target classification and tracking from real-time video[C]//Applications of Computer Vision,Fourth IEEE Workshop on.Princeton,New Jersey:[s.n.],1998:8-14
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views(3321) PDF downloads(1009) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return