On the basis of expounding the basic principle using 2-d wavelet transform for seismic attributes data, the paper built up the effective flow used for multi-scale edge detection of image.
本文在阐明二维小波变换用于地震属性数据基本原理的基础上，建立了小波变换用于图像多尺度边缘检测的有效流程。
It has also important application in seismic data analysis, for example, seismic spectral decomposition, instantaneous attributes extraction, etc.
在地震勘探数据分析中也有重要的应用，如地震频谱分解，瞬时属性提取等。
The volume attributes are to use adjacent domain analysis and multi-channel analysis for computing the attributes for each sub-volume from seismic data volume.
体属性是利用邻域分析及多道滤波等手段从地震数据体中计算出每个子体的属性。
Local structural entropy measure in frequency division is put forward to detect local discontinuities of seismic data, by the virtue of the instantaneous attributes based on wavelet transform.
本文基于小波变换具有多尺度多分辨率分析的优点，提出了在特定的小波变换分频瞬时属性上，利用局部结构熵算法来检测地震数据的局部不连续性。
To achieve this goal, one important approach is to extract and analyze seismic attributes from data.
提取和分析地震波属性是获取所需信息的一条重要途径。
Several typical models were designed to get their seismic synthetic data and their instantaneous attributes were extracted individually.
设计了几组典型模型，用褶积模型制作合成地震记录，然后分别计算它们的瞬时谱属性。
The seismic attributes refer to physical quantities, which are derived from seismic data and related with the geometry, kinematics, dynamics and statistics characteristic of seismic wave.
地震属性是从地震数据中导出的有关地震波的几何学、运动学、动力学和统计学特征的物理量。
The seismic attributes refer to physical quantities, which are derived from seismic data and related with the geometry, kinematics, dynamics and statistics characteristic of seismic wave.
地震属性是从地震数据中导出的有关地震波的几何学、运动学、动力学和统计学特征的物理量。
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