Abstract
As the basic feature of image, edge can be used to identify target, extract feature and provide valuable feature parameters. In the process of image acquisition, transmission and processing, it is inevitable that images will be affected by different degrees of noise. Gaussian noise and salt and pepper noise, as common noises, are often the causes of image blurring and deformation. As the traditional Canny algorithm does not have the disadvantage of removing the salt and pepper noise, this paper adopts the hybrid de-noising method of fuzzy adaptive median filtering and bilateral filtering to remove the salt and pepper noise while achieving the effect of maintaining the edge and smoothing the noise reduction. At the same time, 5 × 5sobel operator and Oust adaptive threshold are selected to better obtain edge information and improve edge connection. The experiment shows that the improved edge detection algorithm is better than the traditional Canny algorithm when adding high-density salt and pepper noise. It can filter out the sundries and identify the subject target.
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Wang, M., Zhang, B.J., Zhang, C.P., Zu **e, J., Wang, F.J. (2021). An Edge Detection Algorithm Based on Fuzzy Adaptive Median Filtering and Bilateral Filtering. In: Liang, Q., Wang, W., Liu, X., Na, Z., Li, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2020. Lecture Notes in Electrical Engineering, vol 654. Springer, Singapore. https://doi.org/10.1007/978-981-15-8411-4_156
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DOI: https://doi.org/10.1007/978-981-15-8411-4_156
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