Structure tensor total variation-regularized weighted nuclear norm minimization for hyperspectral image mixed denoising
详细信息 查看全文
- 作者：Zhaojun Wu ; Qiang Wang ; Jing Jin ; jinjinghit@hit.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Yi Shen
- 关键词：Hyperspectral image denoising ; Low rank ; Structure Tensor Total Variation (STV) ; Nuclear Norm Minimization (NNM) ; Alternating Direction Method of Multipliers (ADMM)
- 刊名：Signal Processing
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：131
- 期：Complete
- 页码：202-219
- 全文大小：5815 K
文摘
- •
Proposed a STWNNM model to exploit global gradient information from all bands.
- •
Use a non-negative, rotationally symmetric kernel to capture local information.
- •
Two different strategies based on ADMM are proposed to solve the STWNNM model. Validate effectiveness of the STWNNM for HSI mixed denoising.