Noise elimination method based on curvelet transform

The random noise has a broad band in seismic record, the conventional de-noise method can not get ideal result. Wavelet transform de-noise method will damage effective signals while pressing random noise and has some limitations in pressing random noise in 2-D signals. Aiming at the limitations, Candè proposed ridge-let transform. But for the whole profile, the ridgelet transform can not obtain ideal result either. Therefore, the curvelet transform is developed, which is a multi-scale geometric analysis method based on wavelet transform and ridgelet transform. The method can display the directional linear singularity edge, and overcome the inherence defects of wavelet transform in showing the directional characteristics of graph edge. The curvelet transform in combination with anisotropy characteristic of ridgelet transform and multi-scale characteristic of wavelet transform can protect effective signals while press random noise and achieve better de-noise result. The de-noise result of simulation data and actual data shows that the curvelet transform is feasible.