Outlier Denoising Using a Novel Statistics-Based Mask Strategy for Compressive Sensing
Abstract
:1. Introduction
2. Methods
2.1. Review of CS Denoising Theory
2.2. A Novel Statistics-Based Mask Function for Outlier Noise
2.3. CS Denoising Algorithm with the Proposed Mask
Algorithm 1 CS denoise based on the CRSI method |
Input: measurement matrix Φtm, measurement data d, Output: signal estimation
|
3. Results
3.1. Synthetic Data
3.2. Marine Data
3.3. Land Field Data
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Wang, W.; Yang, J.; Huang, J.; Li, Z.; Sun, M. Outlier Denoising Using a Novel Statistics-Based Mask Strategy for Compressive Sensing. Remote Sens. 2023, 15, 447. https://doi.org/10.3390/rs15020447
Wang W, Yang J, Huang J, Li Z, Sun M. Outlier Denoising Using a Novel Statistics-Based Mask Strategy for Compressive Sensing. Remote Sensing. 2023; 15(2):447. https://doi.org/10.3390/rs15020447
Chicago/Turabian StyleWang, Weiqi, Jidong Yang, Jianping Huang, Zhenchun Li, and Miaomiao Sun. 2023. "Outlier Denoising Using a Novel Statistics-Based Mask Strategy for Compressive Sensing" Remote Sensing 15, no. 2: 447. https://doi.org/10.3390/rs15020447