Journal of Astronomy and Space Sciences

  • 제33권4호
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  • Pages.313-318
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  • 2016
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  • 2093-5587(pISSN)
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  • 2093-1409(eISSN)
한국우주과학회 (The Korean Space Science Society)
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Edge Detection Method Based on Neural Networks for COMS MI Images

  • 투고 : 2016.08.23
  • 심사 : 2016.11.15
  • 발행 : 2016.12.15
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초록

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

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참고문헌

  1. Bogdanov I, Mirsu R, Tiponut V, Matlab model for spiking neural networks, Proceedings of the 13th WSEAS conference on systems, Rodos Island, Greece, 22-24 Jul 2009.
  2. Canny J, A computational approach to edge detection, IEEE Trans. Pattern Anal. Mach. Intell. PAMI-8, 679-698 (1986). http://dx.doi.org/10.1109/TPAMI.1986.4767851
  3. Long LN, Gupta A, Biologically-inspired spiking neural networks with Hebbian learning for vision processing, Proceedings of the 46th AIAA Aerospace Science Meeting and Exhibit, Reno, NV, USA, 07-10 Jan 2008.
  4. Lu D, Yu XH, Jin X, Li B, Chen Q, et al., Neural network based edge detection for automated medical diagnosis, Proceedings of the IEEE International Conference on Information and Automation, Shenzhen, China, 6-8 Jun 2011.
  5. NASA/GSFC, GOES I-M DataBook (NASA/GSFC, Greenbelt, 1996).
  6. Wu QX, McGinnity M, Maguire L, Belatreche A, Glackin B, Edge detection based on spiking neural network model (Springer Berlin Heidelberg, Heidelberg, 2007).