The second-generation wavelet transform and its application in denoising of seismic data

By S. Cao, Xiang-tao Chen. 2005

69 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Geophysics, Media Technology

View Paper: https://www.semanticscholar.org/paper/7935bc7f6ae4129b60a0fd08226e5c807263257a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Gregory C. Beroza
2. Weiqiang Zhu
3. S. M. Mousavi

In Geophysics

1. S. M. Mousavi
2. Gregory C. Beroza
3. Weiqiang Zhu
4. Siwei Yu
5. Jianwei Ma
6. Y. Sheng
7. P. Martin Mai
8. M. Guatteri

In Media Technology

1. S. M. Mousavi
2. Gregory C. Beroza
3. Weiqiang Zhu

Citations in the corpus

• Seismic Signal Denoising and Decomposition Using Deep Neural Networks (2018, methodology): “…this approach, noisy time series are first transformed into the time-frequency domain using a time-frequency transform, such as a wavelet transform [22, 23, 24, 25, 26, 27], Short Time Fourier Transform (STFT) [28], S-transform [29], curvelet transform [30, 31, 32], dreamlet transform [33],…”