高光谱成像
矩阵范数
秩(图论)
张量(固有定义)
规范(哲学)
计算机科学
人工智能
结构张量
降噪
模式识别(心理学)
数学
算法
图像(数学)
计算机视觉
物理
纯数学
组合数学
特征向量
量子力学
政治学
法学
作者
Pengfei Liu,Lanlan Liu
标识
DOI:10.1109/igarss52108.2023.10283044
摘要
In this paper, we propose a new method for simultaneous hyperspectral image (HSI) destriping and denoising with spectral low-rank and tensor nuclear norm under the tensor framework. Specifically, the tensor nuclear norm is used to model the tensor low-rank property of stripe. Moreover, the nuclear norm is used to model the low-rank property of spectral gradient of HSI. Then, the ADMM algorithm is used to effectively solve the proposed model. Experimental results on simulated HSI dataset and real HSI dataset verify the superiority of the proposed method.
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