Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (16): 142-145.

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Image denoising method based on PDE

CHEN Long, CAI Guangcheng   

  1. Faculty of Science, Kunming University of Science and Technology, Kunming 650500, China
  • Online:2015-08-15 Published:2015-08-14

基于PDE的图像去噪方法

陈  龙,蔡光程   

  1. 昆明理工大学 理学院,昆明 650500

Abstract: According to the shortcoming of P-M nonlinear diffusion model and the self-snake model during the diffusion process, in order to utilize fully advantage of these two models, a novel image denoising method based on mixing self-snake model and P-M diffusion model is proposed, and a fidelity term is added into mixed model. Denoising and edge preserving process can be obtained to a good result. Finally, experiment results show that the proposed method not only remove noise efficiently, but also retain detail information well, such as edges.

Key words: image denoising, self-snake model, Partial Differential Equation(PDE), nonlinear diffusion

摘要: 针对P-M非线性扩散模型以及自蛇模型对图像滤波的不足,为了充分利用两种模型各自的优势,提出了一种新的基于自蛇模型与P-M扩散模型相混合的去噪方法,同时在其扩散方程中添加了忠诚项,这样噪声去除与边缘保留就可以得到一个较好的效果。最后实验结果表明,该方法既能有效去除图像噪声,也能很好地保持图像的边缘等细节信息。

关键词: 图像去噪, 自蛇模型, 偏微分方程(PDE), 非线性扩散