• DocumentCode
    2209588
  • Title

    Mathematical Morphology Edge Detection Algorithm of Remote Sensing Image with High Resolution

  • Author

    Liu Sheng ; Wang Xiaoyu ; Qiu Xinfa ; He Yongjian

  • Author_Institution
    Coll. of Comput. & Software, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
  • fYear
    2009
  • fDate
    26-28 Dec. 2009
  • Firstpage
    1323
  • Lastpage
    1326
  • Abstract
    Based on characteristics of remote sensing images, with high spatial resolutions and mathematical morphology (MM) methods, MM edge detection algorithm were developed to process remote sensing images using multi-scale omni-directional structure elements. In this algorithm, the peak signal-to-noise ratio (PSNR) technique was created to acquire the self-adaptive scale weights and replace the method with fixed mean. Results suggest that: the purposed algorithms, compared with the traditional Canny edge detection operator and MM edge detection algorithm with simplex scale figure structure elements, can successfully resolve the contradictions between noise suppression and extraction of fine edge excellently, and anti-noise performance is strong. The image edge information can be used in extraction geometrical and texture features.
  • Keywords
    edge detection; feature extraction; geophysical image processing; image resolution; image texture; mathematical morphology; noise; remote sensing; anti-noise performance; fine edge extraction; geometrical feature extraction; high spatial resolutions; mathematical morphology edge detection algorithm; multiscale omni-directional structure elements; noise suppression; peak signal-to-noise ratio technique; remote sensing image; self-adaptive scale weights; texture feature extraction; Data mining; Feature extraction; Image edge detection; Image resolution; Information science; Morphology; PSNR; Remote sensing; Software algorithms; Spatial resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2009 1st International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4909-5
  • Type

    conf

  • DOI
    10.1109/ICISE.2009.730
  • Filename
    5454598