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Volume 30 Issue 12
Jan.  2011
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Zhao Chun-Hui, Shang Zheng-Guo. New FRIT Denoisy Method Based on Compact Energy Delamination[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2894-2897. doi: 10.3724/SP.J.1146.2007.00973
Citation: Zhao Chun-Hui, Shang Zheng-Guo. New FRIT Denoisy Method Based on Compact Energy Delamination[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2894-2897. doi: 10.3724/SP.J.1146.2007.00973

New FRIT Denoisy Method Based on Compact Energy Delamination

doi: 10.3724/SP.J.1146.2007.00973
  • Received Date: 2007-06-15
  • Rev Recd Date: 2007-12-13
  • Publish Date: 2008-12-19
  • The Finite Ridgelet Transform (FRIT) is a new image processing method which could conquer the defect of Wavelet in high dimension. The method changes the line singularity in the image into the point singularity via the Radon transform, deals the point singularity with Wavelet transform. It is shown that the energy is compact by using the Radon transform on the image, and the characteristic on the Ridgelet transform is applied in the image processing which obtains the good result in the denoising and the edge keeping of the image. Especially under the strong noisy, it is better than other methods.
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  • [1] Bberger Cs. Self-tuning control of offset using a movingaverage filter. IEEE proceedings. Part D. Control theory andapplications, 1985, 133(44): 184-188. [2] Pitas I and Venetsanopoulos A N. Nonlinear Digital Filters:Principles and Applications. Boston: Kluwer AcademicPublishers, 1990: 171-177. [3] Gunawan D. Denoising images using wavelet transform.Proceedings of the IEEE Pacific Rin Conference onCommunications, Computers and Signal. Victorria BC, USA,1999: 83-85. [4] Donoho D L and Johnstone I M. Ideal spatial adaptation viawavelet shrinkage. Biometrika, 1994(81): 425-455. [5] Hou Biao, Jiao Li-cheng, and Liu Fang. Image denoisingbased on ridgelet. Signal Processing, 2002 6th InternationalConference on Signal Processing, Beijing, 26-30 Aug. 2002(1):780-783. [6] Cands E J and Donoho D L. Ridgelet: a key to higherdimensionalintermittency[J].Phil. Trans. R Soc lond A.1999,357(1760):2495-2509 [7] Cands E J. Ridgelets: Theory and applications. Departmentof Statistics, Stanford University, 1998: 23-38. [8] Minh N D and Vetterli M. The finite Ridgelet transform forimage representation. IEEE Trans. on Image Processing, 2003:12(1): 16-28.
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