Application of anisotropic filtering algorithm in seismic curvature attribute
各向异性滤波算法在地震曲率属性中的应用

It is necessary to have denoising pretreatment for images before the calculation of curvature attribute. However, when eliminating noise, conventional methods of image filtering would meanwhile smear the image features such as edges, lines and textures; while the P-M model based on partial differential equations would lead to blocking effects in the smoothing process. In order to solve these problems, this paper proposed an anisotropic filtering pretreatment based on tensor diffusion, which would get abundant information about the local structure of an image by defining the scatter matrix, and then used these structures to control the diffusion process so as to achieve better image filtering. The theoretical analysis and experimental results show that compare to several general algorithms of image filtering, anisotropic filtering can make the result of curvature attribute clearer and higher in quality.