NDLI: The Impact of Noise or Noiseless on Cellular Neural Network to Detect Image Edge

Content Provider	IEEE Xplore Digital Library
Author	Zhen Tong Guo-Dong Li Wen-Xia Xu
Copyright Year	2014
Description	Author affiliation: Xinjiang Weather Modification Office, Urumqi, China (Wen-Xia Xu) \|\| Xinjiang Univ. of Finance & Econ., Urumqi, China (Zhen Tong; Guo-Dong Li)
Abstract	This paper argues that the best effect to remove Gaussian noise is to use wiener filtering, and to remove salt & pepper noise to use median filtering will get a better effect. By using the correlation index, and through the original image adding noise and removing noise, it calculates the correlation index of the removal-noise image of the original image is better than traditional methods which used as average filtering and median filtering and wiener filtering to delete the noise of an image. Specifically, this research paper puts forward two results: one is to provide the add noise image first and then to remove the noise, and then to use CNN to detect the image edge, the other is to provide the noise image first by using CNN to detect edge and then to remove the noise. Via these two results compared with the result of the original image edge detection, the conclusion will be as following: in order to avoiding the impact of noise bring to an image, before the image edge detect, one must deal with the noise first.
Starting Page	1056
Ending Page	1059
File Size	306263
Page Count	4
File Format	PDF
e-ISBN	9781479942619
DOI	10.1109/ISDEA.2014.233
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation coefficient Wiener filters CNN Filtering Correlation index Image edge detection Gaussian noise Noise Edge detection
Content Type	Text
Resource Type	Article

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