This paper puts forward a new edge-directed enhancing based anisotropic diffusion model.
本文提出了一个新的边缘定向增强扩散模型。
After that we studied several Post-processing models based on PDE of Anisotropic Diffusion, including Directional Diffusion and Self-Snake model.
进而深入研究了经典的基于偏微分方程的后处理方法，包括方向扩散，自蛇模型等非线性扩散方程。
In this paper we propose a new ultrasound image segmentation scheme for segmentation of low SNR ultrasound images, which consisted of anisotropic diffusion function and snake model.
为了对低信噪比的超声图像进行有效分割，提出了一种新的超声图像分割方案，该方案由各向异性扩散方程和蛇模型组成。
The improved model not only detects effectively the detailed edges in images, but also preserves the stability of anisotropic diffusion.
实验结果表明，该方法不仅能够更有效地识别噪声图像中的细节边缘，而且还保证了各向异性扩散模型的稳定性；
The improved model not only detects effectively the detailed edges in images, but also preserves the stability of anisotropic diffusion.
实验结果表明，该方法不仅能够更有效地识别噪声图像中的细节边缘，而且还保证了各向异性扩散模型的稳定性；
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