**6. Conclusions**

We introduced an accurate noise or signal removal algorithm based on SS-CWT. The performance of this algorithm was tested with actual passive seismic data acquired in a certain area of Sichuan, China. The results show that this algorithm can not only eliminate unnecessary prominent coherent noise events in the original passive seismic data but can also denoise the correlogram formed after cross-correlation calculation, improve the S/N of the restored Green function, and enable the reconstruction of a high-fidelity Green function from short time series. However, the computational efficiency of this method is low, and it may not be able to achieve good application results on datasets that are greatly disturbed by human activities.

**Author Contributions:** Methodology, J.F. and G.L.; validation, J.F., G.L. and Y.L.; writing—original draft preparation, J.F.; writing—review and editing, J.F. and Y.L.; supervision, G.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the National Natural Science Foundation of China (grant no. 42074131).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Acknowledgments:** We thank the editors and four anonymous reviewers for their careful reviews and constructive comments.

**Conflicts of Interest:** The authors declare no conflict of interest.
