摘要
讨论了一种基于非线性扩散方程的图像去噪方法.在讨论了图像去噪的3个基本要求的基础上,总结了平均曲率运动去噪模型和总变差去噪模型中利用保真项的不足.将利用图像的局部信息构造的自适应保真项引入到方向扩散去噪模型中,克服了原有方法在耦合保真项上的不足,使新的非线性扩散去噪模型能够在有效地去除噪声的同时很好地保持目标尖角、边缘等重要的几何结构.实验结果表明,耦合自适应保真项的扩散方程能够很好地保持图像中目标的几何结构,同时具有良好的去噪能力.
A new anisotropic diffusion based image denoising method is proposed in three requirements of image denoising are proposed, based on which the defect of the this work. At first, fidelity term used in the mean curvature motion model and that in the total variation based image denoising models are investigated. After that, a new coupling adaptive fidelity term, which is obtained from image local structural information, is proposed for the diffusion based image denoising. Experimental results show that the denoising method with our new fidelity term is capable of sufficiently preserving geometric information such as edges and corners in addition to its effectiveness for image denoising.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2006年第10期1519-1524,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
香港特区政府研究资助局(CUHK/1/00C)
关键词
平均曲率运动
总变差模型
保真项
图像去噪
mean curvature motion
total variation model
fidelity term
image denoising
