基于灰度值数学形态算子处理的各向异性扩散

在各向异性扩散去噪音处理中，目前的正则化方法不能阻止国像边界和角的退化介绍了在非线性扩散方程中应用灰度值侵蚀和渐进正则化尺度的新算法．它能在有效地去噪音的同时保持边界和角的局域性另外在扩散方程离散化中，用形态算于梯度代替中心差商梯度，对于图像中的单像素点的线条．前者不能增强而后者则能有效地增强最后分别给出了两种算法的增强图像的例子。

Anisotropic Diffusion Filtering Based Gray-value Morphological Operator Processes

Current regularization formulations of anisotropic diffusion denoising processes are unable to prevent degradation of edges and corners. It introduces a novel algorithm that applies gray-value erosion and gradual regularization scale in anisotropic diffusion filtering. It is capable of denoising efficiently while maintaining edge and corners locality. Another idea is to replace central difference gradient by morphological gradient in diffusion coefficient discretization, the latter applying in anisotropic diffusion can enhance one-pixel line feature in noisy image while the former can not process efficiently. Results are presented that demonstrate their efficacy in heavy noisy image denoising and single pixel line enhancing tasks respectively.