.png){kind=icon}
返回
Hyperspectral Image Denoising Using Nonconvex Fraction Function
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2023.3307411.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Hyperspectral image (HSI) denoising is a challenging task, not only because it is unavoidably contaminated by severe mixed noises, but also because of its hard-to-recover spatial-spectral structure. Since it has been found that HSI has low-rank property, low-rank models have received extensive attention in dealing with the HSI denoising task. However, these models either use nuclear norm, which can only obtain suboptimal solutions, or require some predefined information that is difficult to determine. To address these issues, in this letter, we propose a new HSI denoising model based on nonconvex fraction function, which has excellent performance in removing mixed noises. Specifically, the proposed model can capture the rank information of HSI automatically, which allows it to separate clean HSI from noises more accurately. Then, an iterative optimization algorithm is developed by exploiting the framework of the augmented Lagrange multiplier (ALM). Meanwhile, the subproblems at each iteration can be solved by the proximal operator with a closed-form solution. Besides, the convergence of the proposed algorithm is also provided theoretically. Extensive experiments implemented with simulated and real datasets demonstrate that our proposed model performs better than state-of-the-art models in HSI denoising. MATLAB code is available at https://github.com/wangzhi-swu/HSI-Denosing.
Keyword:
Denoising
hyperspectral image (HSI)
low-rank
nonconvex fraction function
期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
机构
引用论文
Using Minimum Component and CNN for Satellite Remote Sensing Image Cloud Detection基于最小分量和CNN的卫星遥感图像云检测
OAAI
OAAI分享收藏Image denoising via sparse and redundant representations over learned dictionaries通过学习字典上的稀疏和冗余表示进行图像去噪
PREAI
分享收藏Temperatura do solo sob três condições de cobertura em Londrina, Paranavaí e Guarapuava, no estado do Paraná.png)
Agrometeoros
OAAI
AgrometeorosIF0
OAAI分享收藏Denoising of Hyperspectral Images Using Nonconvex Low Rank Matrix Approximation基于非凸低秩矩阵逼近的高光谱图像去噪
PREAI
分享收藏分享收藏
查看更多内容