Anisotropic Diffusion Model Based on Generalized Metric in Sobolev Space
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摘要: 给出了Sobolev空间的一种广义度量, 在该度量下提出了一个新的各向异性增强、扩散方程. 广义度量中的变系数, 较好地控制了方程的扩散行为, 使得新模型不仅能有效增强图像的细节特征, 而且能在噪声去除和边缘保护之间取得较好的平衡, 同时给出了相应的隐式离散算法. 仿真实验结果表明, 新模型和算法是行之有效的.Abstract: A generalized metric is defined in Sobolev space, based on which an anisotropic sharpening/diffusion equation is presented. Since the space-varying coefficient of the generalized metric can control the diffusion behavior better, the proposed model can not only highlight the image detail effectively but also achieve a good balance between noise removal and edge preservation. The corresponding implicit algorithm is then developed. Simulation results show that the new model and algorithm are feasible.
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