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Research Article | Open Access |

Edge Detection in Satellite Image Using Cellular Neural Network

Author 1: Osama Basil Gazi Author 2: Dr. Mohamed Belal Author 3: Dr. Hala Abdel-Galil
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 5, No. 10 · Published 2014 · Cited by 14

DOI: https://doi.org/10.14569/IJACSA.2014.051010

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Abstract

The present paper proposes a novel approach for edge detection in satellite images based on cellular neural networks. CNN based edge detector in used conjunction with image enhancement and noise removal techniques, in order to deliver accurate edge detection results, compared with state of the art approaches. Thus, considering the obtained results, a comparison with optimal Canny edge detector is performed. The proposed image processing chain deliver more details regarding edges than canny edge detector. The proposed method aims to preserve salient information, due to its importance in all satellite image processing applications.

Keywords

cellular neural network liner matrix inequality differential evolution genetic algorithm Field-programmable gate array partial differential equation

How to Cite this Article

Gazi, O. B., Belal, D. M., & Abdel-Galil, D. H. (2014). Edge Detection in Satellite Image Using Cellular Neural Network. International Journal of Advanced Computer Science and Applications, 5(10). https://doi.org/10.14569/IJACSA.2014.051010

Gazi, Osama Basil, et al.. "Edge Detection in Satellite Image Using Cellular Neural Network." International Journal of Advanced Computer Science and Applications, vol. 5, no. 10, 2014, https://doi.org/10.14569/IJACSA.2014.051010.

@article{Gazi2014,
  title     = {Edge Detection in Satellite Image Using Cellular Neural Network},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {5},
  number    = {10},
  year      = {2014},
  publisher = {The Science and Information Organization},
  author    = {Osama Basil Gazi and Dr. Mohamed Belal and Dr. Hala Abdel-Galil},
  doi       = {10.14569/IJACSA.2014.051010},
  url       = {https://doi.org/10.14569/IJACSA.2014.051010}
}

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