基于扩散滤波的多尺度分解和重构方法及应用初探

Multi-scale Decomposition and Reconstruction Based on Diffusion Filtering and Preliminary Application

从各向异性PM方程出发,推导多维扩散滤波微分方程的离散格式及其稳定性条件,首次构建基于扩散滤波的多尺度分解和重构方法,给出两种具体实施方案及其关键步骤.地震资料应用表明,所提方法分解和重构信号的过程合理可靠,其中方案①的2D傅里叶波数谱能量随尺度的增加而远离谱中心点,其残差信号表现为高波数信号,在随机噪声压制中取得了较好的效果;方案②的2D傅里叶波数谱能量随尺度的增加而靠近谱中心点,其残差信号表现为低波数信号,在低频逆时噪声压制中取得了较好的效果.所提方法计算过程简单易实现,对于信号处理提供了一种多尺度分解和重构方法,在地震信号处理领域具有较高的应用价值.

From PM equation we derive muhi-dimensionay diffusion filtering equation discrete formula and its stable condition. We construct multi-scale decomposition and reconstruction method based on diffusion filtering, and provide two specific implementation plans. Application in practical seismic data shows that the method is reasonable and reliable. In the first plan 2D Fourier wave-number spectrum main energy is away from spectrum center with increase of scale, and residual signal acts at high wave numbers, which shows perfect application in random noise suppression. In the second plan 2D Fourier wave-number spectrum energy is close to spectrum center with increase of scale, and residual signal acts at low wave numbers, which shows perfect application in low-frequency reverse time migration noise suppression. The method computation is simple and easy to implement. It provides a multi-scale decomposition and reconstruction method for signal processing. It may has great application in seismic signal processing.