EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 232 (2018) MATEC Web Conf., 232 (2018) 03029 References
Open Access
Issue
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
Article Number 03029
Number of page(s) 6
Section Algorithm Study and Mathematical Application
DOI https://doi.org/10.1051/matecconf/201823203029
Published online 19 November 2018
  1. Chen P, Qian H, Zhu M. Fast Gaussian particle filtering algorithm[J]. Journal of Huazhong University of Science & Technology, 2008. [Google Scholar]
  2. Elad M. On the origin of the bilateral filter and ways to improve it.[J]. Image Processing IEEE Transactions on, 2002, 11(10): 1141-1151. [Google Scholar]
  3. Bai Junqi. Algorithm for Infrared Image Noise Filtering Based on Anisotropic Diffusion[J]. Acta Optica Sinica, 2008, 28(5): 866-869. [CrossRef] [Google Scholar]
  4. Huang T, Yang G, Tang G. A fast two-dimensional median filtering algorithm[J]. IEEE Trans.on Acoustic.speech. & Signal Processing, 1979, 27(1): 13-18. [CrossRef] [Google Scholar]
  5. Xu Yong. Research on image filtering algorithm for edge structure retention type [D]. Hefei, Anhui: Hefei University of Technology, 2011. [Google Scholar]
  6. Buades A, Coll B, Morel J M. A non-local algorithm for image denoising[C]// Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. IEEE, 2005:60-65 vol. 2. [Google Scholar]
  7. Goossens B, Luong H Q. A fast non-local image denoising algorithm[J]. 2008, 6812:81210-81210. [Google Scholar]
  8. Yan Nana. Research on Degraded Image Restoration Technology Based on Non-local Mean [D]. Qinhuangdao City, Hebei Province: Yanshan University, 2011. [Google Scholar]
  9. Kervrann C.,Boulanger J.,and Coupe P. Bayesian non-local means filter, imageredundancy and adaptive dictionaries for noise removal. Proceedings of International Conference on Scale Space Methods Variational Methods Computer Vision,2007,520-532. [CrossRef] [Google Scholar]
  10. Kervrann C.,Boulanger J.,and Coupe P. Bayesian non-local means filter, image redundancy and adaptive dictionaries for noise removal. Proceedings of International Conference on Scale Space Methods Variational Methods Computer Vision,2007,520-532. [CrossRef] [Google Scholar]
  11. Biao Hou, Shang Ronghua, Li Yongwei, et al. Implementation method based on Bayesian non-local mean filter:CN 101661611 A[P]. 2010. [Google Scholar]
  12. Tasdizen T. Principal neighborhood dictionaries for nonlocal means image denoising. IEEE Transactions on Image Processing, 2009, 18(12): 2649-2660. [CrossRef] [Google Scholar]
  13. Zheng Yuhui, Sun Quansen, Xia Deshen. Effective non-local filtering method based on 2DPCA. Acta Automatica Sinica, 2010, 36(10): 1379-1389. [CrossRef] [Google Scholar]
  14. Grewenig S, Zimmer S and Weickert J. Rotationally invariant similarity measures for nonlocal image denoising, Journal of Visual Communication and Image Representation, 2011,22:117-130. [CrossRef] [Google Scholar]
  15. Yan R., Shao L., Cvetkovic S. D., and Klijn J. Improved nonlocal means based on pre-classification and invariant block matching. IEEE/OSA Journal of Display Technology, 2012, 8(4): 212-218. [CrossRef] [Google Scholar]
  16. Sun Weifeng, Peng Yuhua. An improved non-local average denoising method. Chinese Journal of Electronics, 2010, 38(4): 923-928. [Google Scholar]
  17. Thaipanich T., Oh. B. T., Wu P. H., Xu D., and Kuo C. C. J. Improved image denoising with adaptive nonlocal means(ANL-means) algorithm. IEEE Transactions on Consumer Electronics, 2010, 56(4): 2623-2630. [CrossRef] [Google Scholar]
  18. Deledalle C. A., Duval V., and Salmon J. Non-local methods with shape-adaptive patches(NLM-SAP). Journal of Mathematical Imaging Vision, 2011,1-18. [Google Scholar]
  19. Brox T., Kleinschmidt O., and Cremers D. Efficient nonlocal means for denoising of textural patterns. IEEE Transactions on Image Processing,2008, 17(7): 1083-1092. [CrossRef] [Google Scholar]
  20. Dabov K., Foi A., Kakovnik V., and Egiazarian K. Image denoising by sparse 3-D transform-domain cllaborative filtering. IEEE Transactions on Image Processing,2007, 16(8): 2080-2095. [CrossRef] [Google Scholar]
  21. Zhong H., Yang C., and Zhang X. A new weight for nonlocal means denoising using method noise. IEEE Signal Processing Letters,2012, 19(8): 535-538. [CrossRef] [Google Scholar]
  22. Maleki A., Narayan M., an Baraniuk R. G. Anisotropic nonlocal means denoising Applied and Computational Harmonic Analysis,2012(in press). [Google Scholar]
  23. Buades A., Coll B., and Morel J. M. A non-local algorithm for image denoising. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2005:70-74. [Google Scholar]
  24. Hore A, Ziou D. Image quality metrics: PSNR vs. SSIM[C]// International Conference on Pattern Recognition. IEEE, 2010:2366-2369.Hore A, Ziou D. Image Quality Metrics: PSNR vs. SSIM[C]// International Conference on Pattern Recognition. IEEE, 2010:2366-2369. [Google Scholar]
  25. Guo Y, Wang Y, Hou T. Speckle filtering of ultrasonic images using a modified non local-based algorithm[J]. Biomedical Signal Processing & Control, 2011, 6(2): 129-138. [CrossRef] [Google Scholar]
  26. Yan Yubing, Zhang Qishan, Yan Yunping. Image quality evaluation model based on PSNR and SSIM [J]. Journal of Image and Graphics, 2006 (12): 1758-1763. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.