Seismic data restoration via data-driven tight frame

By Jingwei Liang, Jianwei Ma, Xiaoqun Zhang. 2014

97 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/13582f31abfc91be6056dd5b68465097fd41377f

How researchers see this paper

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

1. Siwei Yu
2. Jianwei Ma
3. Xiaoqun Zhang
4. Mauricio D. Sacchi
5. Jingwei Liang
6. Guochang Liu
7. Xiaohong Chen
8. Neal Parikh

Citations in the corpus

• Interpolation and denoising of high-dimensional seismic data by learning a tight frame (2015, methodology): “Construction method for 1D wavelet tight frame is illustrated in Cai et al., 2014 and Liang et al., 2014.”
• Deep Learning for Geophysics: Current and Future Trends (2021, methodology): “Can the entire dictionary be updated by one SVD for efficient improvement? A data-driven tight frame (Cai et al., 2014; Liang et al., 2014) was proposed by enforcing a tight frame constraint on the dictionary W.”