Name
Title | ||
|---|---|---|
Low rank constraint and spatial spectral total variation for hyperspectral image mixed denoising. |
Abstract | ||
|---|---|---|
•We propose a novel low rank and spatial spectral total variation based HSI mixed denoising model.•The reason of undesirable jagged distortion caused by the band by band TV regularization is analyzed.•The model can jointly utilize global low rank and local spatial spectral smooth properties of HSI.•The iterations based on the ADMM are carried out to solve the optimization problem effectively.•The proposed model can effectively suppress the jagged distortion while removing the noise. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.sigpro.2017.06.012 | Signal Processing |
Keywords | Field | DocType |
Hyperspectral image denoising,Low rank,Spatial spectral total variation,Alternating Direction Method of Multipliers (ADMM) | Noise reduction,Mathematical optimization,Matrix norm,Hyperspectral imaging,Regularization (mathematics),Total variation denoising,Distortion,Optimization problem,Gaussian noise,Mathematics | Journal |
Volume | Issue | ISSN |
142 | C | 0165-1684 |
Citations | PageRank | References |
3 | 0.37 | 28 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiang Wang | 1 | 601 | 84.65 |
| Zhaojun Wu | 2 | 17 | 4.27 |
| Jing Jin | 3 | 14 | 2.50 |
| Tiancheng Wang | 4 | 3 | 0.37 |
| Yi Shen | 5 | 163 | 25.21 |