关键词: 各向异性扩散, 超声图像, 斑点噪声, 局部方差, 图像去噪, 特征保留

Abstract: Since the anisotropic diffusion methods cannot make a distinction between strong noise and weak edge effectively, the authors proposed an improved anisotropic diffusion denoising method based on local statistical characteristics. While denoising images by anisotropic diffusion method, points with large gray-level variations were found by using gradient threshold, and whether the point was a noise point or not was judged by calculating local variance and local deleted variance, and then mean filtering was used for the noise points. The experiments upon simulation images and clinical ultrasonic images show that this method preserves features and edges more efficiently than traditional anisotropic diffusion methods while denoising images.

Key words: anisotropic diffusion, ultrasonic image, speckle noise, local variance, image denoising, feature preserving