【摘要】 针对Perona和M alik各向异性扩散方程不能保留细节边缘的缺点,提出了一个基于形态学算子的各向异性扩散方程.新的各向异性扩散方程在计算扩散系数时,不只是考虑了图像的梯度,还考虑了二阶导数,并在作用形态学闭开算子后的图像上估计各阶导数.这样,该算子不但能够有效地去除噪声,还能保持图像中的尖峰和窄边缘,从而更好地保持边缘位置.实验结果表明用该算子处理后的图像具有较高的清晰度和对比度.而且该算子对于高斯白噪声图像的处理效果也相当理想.更多还原

【Abstract】 An anisotropic diffusion equation based on the morphological operator is proposed to make up for the defeat of the generalized PM diffusion not to preserve edge details.Its diffusion coefficient is dependent not only on the gradient of the image,but also on the second derivatives estimated on the image after being applied to the morphological close-open operator.The new operator is capable of removing noise efficiently and preserving the edge locality and thin edges.Experiments show that the processed images have high fidelity and constrast and that the new operator has an advantage of removing noise in images with heavy Gaussian noise.更多还原