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Mathematical Problems in Engineering
Volume 2017, Article ID 4065306, 11 pages
https://doi.org/10.1155/2017/4065306
Research Article

A New Image Denoising Method Based on Adaptive Multiscale Morphological Edge Detection

1School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China
2Institute of Petroleum and Chemical Industry, Shenyang University of Technology, Shenyang, Liaoning 110870, China

Correspondence should be addressed to Gang Wang; nc.ude.uen.esi@gnawgnag

Received 18 August 2016; Revised 29 January 2017; Accepted 2 March 2017; Published 5 April 2017

Academic Editor: Lotfi Senhadji

Copyright © 2017 Gang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [7 citations]

The following is the list of published articles that have cited the current article.

  • Yanbo Li, and Junping Wang, “Novel Binary Adaptive Morphological Operators,” 2018 12th IEEE International Conference on Anti-counterfeiting, Security, and Identification (ASID), pp. 132–135, . View at Publisher · View at Google Scholar
  • Fatma S. Abousaleh, Neng-Hao Yu, Kai-Lung Hua, and Wen-Huang Cheng, “Medical image denoising using sparse representations,” 2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST), pp. 422–427, . View at Publisher · View at Google Scholar
  • Wenkui Xi, Tonghai Wu, Ke Yan, Xujun Yang, Xiangjun Jiang, and Ngaiming Kwok, “Restoration of online video ferrography images for out-of-focus degradations,” EURASIP Journal on Image and Video Processing, vol. 2018, no. 1, 2018. View at Publisher · View at Google Scholar
  • Gagarina, Zhertunova, and Yanakova, “Adaptive denoising algorithm based on nonlocal means in image processing,” 2018 International Russian Automation Conference, RusAutoCon 2018, 2018. View at Publisher · View at Google Scholar
  • Yue Wang, Qi Zhang, Yang Lu, Jiaqi Li, Di Wang, and Wei Dong, “A novel method of Brillouin scattering spectrum identification based on Sobel operators in optical fiber sensing system,” Optical and Quantum Electronics, vol. 50, no. 1, 2018. View at Publisher · View at Google Scholar
  • Suresh, and Elavaar Kuzhali, “Patch-based denoising with K-nearest neighbor and SVD for microarray images,” Advances in Intelligent Systems and Computing, vol. 763, pp. 132–147, 2019. View at Publisher · View at Google Scholar
  • Madhu Golla, and Sudipta Rudra, “A Novel Approach of K-SVD-Based Algorithm for Image Denoising,” Histopathological Image Analysis in Medical Decision Making, pp. 154–180, 2019. View at Publisher · View at Google Scholar