| 基于PDE的图像去噪方法 |
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| 引用本文： | 陈龙,蔡光程.基于PDE的图像去噪方法[J].计算机工程与应用,2015,51(16):142-145. |
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| 作者姓名： | 陈龙 蔡光程 |
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| 作者单位： | 昆明理工大学 理学院，昆明 650500 |
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| 基金项目： | 云南省自然科学基金(No.2011FZ025)；昆明理工大学人才基金(No.2008-72)；昆明理工大学研究生核心课程项目。 |
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| 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。
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| 关 键 词： | 图像去噪 自蛇模型 偏微分方程（PDE） 非线性扩散 |
Image denoising method based on PDE |
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| CHEN Long,CAI Guangcheng.Image denoising method based on PDE[J].Computer Engineering and Applications,2015,51(16):142-145. |
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| Authors: | CHEN Long CAI Guangcheng |
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| Affiliation: | Faculty of Science, Kunming University of Science and Technology, Kunming 650500, China |
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| 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. |
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| Keywords: | image denoising self-snake model Partial Differential Equation(PDE) nonlinear diffusion |
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