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计算机工程 ›› 2008, Vol. 34 ›› Issue (15): 196-198. doi: 10.3969/j.issn.1000-3428.2008.15.071

• 人工智能及识别技术 • 上一篇    下一篇

基于离散小波阈值的偏微分图像去噪

刘晨华1,2,冯象初1,张力娜1   

  1. (1. 西安电子科技大学理学院数学系,西安 710071;2. 太原科技大学应用科学学院数学系,太原 030024)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-08-05 发布日期:2008-08-05

Image Denoising of PDE Based on Discrete Wavelet Threshold

LIU Chen-hua1,2, FENG Xiang-chu1, ZHANG Li-na1   

  1. (1. Department of Mathematic, School of Science, Xidian University, Xi’an 710071; 2. Department of Mathematic, Application Science Institute, Taiyuan University of Science and Technology, Taiyuan 030024)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-08-05 Published:2008-08-05

摘要: 小波方法和偏微分方程方法是图像去噪中的主要方法。该文提出基于离散小波变换对图像进行阈值去噪,得出了小波阈值的偏微分方程表示形式,在此基础上研究偏微分方程的解法,采用分数步的小波阈值方法对图像去噪,得到了较好的去噪效果,同时可以保护边缘。数值试验结果表明,该方法具有比小波方法更好的去噪效果,能获得较高的信噪比。

关键词: 离散小波变换, 阈值, 偏微分方程, 图像去噪

Abstract: Wavelet and Partial Differential Equation(PDE) are the main methods in removing image noise. Image noise is removed by making use of discrete wavelet threshold transform. The expression form of PDE based on wavelet threshold is obtained. It adapts the method of fractional steps wavelet shrinkage for the solution of PDE based on above approach. It can receive better effect of image denoising and attain the purpose of preserving edge and smoothing noise. Experimental results show that the new method can obtain better effect and higher SNR than wavelet method.

Key words: discrete wavelet transform, threshold, Partial Differential Equation(PDE), image denoising

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