Generalized Logarithmic Tensor Nuclear Norm for Hyperspectral-Multispectral Image Fusion via Tensor Ring Decomposition

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 18; pp. 16596 - 16608
• Main Authors: Zhang, Jun, He, Mengling, Deng, Chengzhi
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Computer vision; Correlation; Decomposition; Effectiveness; Estimation; Fourier transforms; Generalized logarithmic tensor nuclear norm (GLTNN); hyperspectral and multispectral image fusion; Hyperspectral imaging; Image resolution; Logarithms; Matrix decomposition; Modes; Permutations; proximal alternating minimization (PAM); Sparse matrices; Spatial resolution; tensor ring (TR) decomposition; Tensors; Water resources

The fusion of a low-spatial-resolution hyperspectral image (LR-HSI) and a high-spatial-resolution multispectral image (HR-MSI) is an effective way to generate a high-resolution hyperspectral image (HR-HSI). In recent years, methods based on tensor ring (TR) decomposition have received widespread att...