.png){kind=icon}
.png){kind=icon}
Return
Seismic random noise attenuation using structure-oriented 3D curvelet transform
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cageo.2025.106020.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• A new method using 3D curvelet transform with dip information to analyze local feature complexity for improved noise suppression. • Adapts constraints based on local complexity: strong thresholds for low-complexity areas (aggressive noise removal), weak thresholds for high-complexity areas (signal preservation). • Outperforms traditional global/multi-scale thresholding in preserving large-dip features while suppressing noise.
Keywords:
3D curvelet transform
dip information
local feature complexity
noise suppression
adaptive thresholding
Journal
C
IF:
4.4
Papers:
5.0K
Citations:
1.5W