MATamf is a Matlab package for the advanced median filter (AMF) for improving the signal-to-noise ratio of seismological datasets. The MaATamf package has a variety of applications in exploration and earthquake seismology.
The demos folder contains all the testing scripts of MATamf on a variety of seismological datasets, reproducing all figures presented in the paper. The description of each testing script can be found below:
test_amf_synlcre.m This script demonstrates the denoising performance on 2D synthetic seismic data containing linear and curved events corrupted by random and strong erratic noise.
test_amf_rs.m This script demonstrates the denoising performance on pre-stack and post-stack 2D real reflection seismic data contaminated by erratic and random noise.
test_amf_das1.m This script demonstrates the denoising performance on 2D raw DAS seismic data corrupted by a mixture of strong noise.
test_amf_das2.m This script demonstrates the adaptability of the proposed method for weak and strong DAS seismic signal denoising.
test_amf_rf.m This script shows the application of the AMF method to improving receiver function imaging.
test_amf_ssp.m This script shows the application of the AMF method to enhance the SS precursor signals arising from the earth’s mantle transition zone discontinuities.
test_amf_sosvmf_somf_mf.m This script is used to conduct a comparison of the denoising performance between the MF, SOMF, SOSVMF, and the proposed AMF methods.
test_amf_bp_sosvmf_ct_drr_syn.m This script demonstrates the denoising performance of different methods on 2D synthetic containing linear and curved events, corrupted by random and strong erratic noise.
test_amf_bp_sosvmf_ct_drr_rs.m This script demonstrates the denoising performance of different methods on 2D raw reflection seismic data.
test_amf_bp_sosvmf_ct_drr_rf.m This script demonstrates the denoising performance of different methods on 2D receiver function data.
test_amf_bp_sosvmf_ct_drr_ssp.m This script demonstrates the denoising performance of different methods on 2D SS precursor data.
test_amf_bp_sosvmf_fk_ct_drr_das.m This script demonstrates the denoising performance of different methods on DAS data.
Oboué, Y.A.S.I, Y. Chen, S. Fomel, and Y. Chen, 2023, An advanced median filter for improving the signal-to-noise ratio of seismological datasets Computer & Geosciences, under review.
Wang, H., Chen, Y., Saad, O.M., Chen, W., Oboué, Y.A.S.I., Yang, L., Fomel, S. and Chen, Y., 2022. A Matlab code package for 2D/3D local slope estimation and structural filtering. Geophysics, 87(3), pp.F1–F14.
Huang, G., M. Bai, Q. Zhao, W. Chen, and Y. Chen, 2021, Erratic noise suppression using iterative structure-oriented space-varying median filtering with sparsity constraint, Geophysical Prospecting, 69, 101-121.
Chen, Y., S. Zu, Y. Wang, and X. Chen, 2020, Deblending of simultaneous-source data using a structure-oriented space varying median filter, Geophysical Journal International, 222, 1805-1723.
Zhao, Q., Q. Du, X. Gong, and Y. Chen, 2018, Signal-preserving erratic noise attenuation via iterative robust sparsity-promoting filter, IEEE Transactions on Geoscience and Remote Sensing, 56, 1558-0644.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details: http://www.gnu.org/licenses/
For any questions regarding the package, please contact Yangkang Chen (chenyk2016@gmail.com) or Innocent Oboue (obouesonofgod1@gmail.com).