1 citations · 1 across the 6 of their papers we have counts for
6 papers
Hyperspectral Super-Resolution with Inter-Image Variability via Degradation-based Low-Rank and Residual Fusion Method
Yue Wen, Kunjing Yang, Minru Bai
The fusion of hyperspectral image (HSI) with multispectral image (MSI) provides an effective way to enhance the spatial resolution of HSI. However, due to different acquisition con…
Implicit Multiple Tensor Decomposition
Kunjing Yang, Libin Zheng, Minru Bai
Recently, triple decomposition has attracted increasing attention for decomposing third-order tensors into three factor tensors. However, this approach is limited to third-order te…
MAUGIF: Mechanism-Aware Unsupervised General Image Fusion via Dual Cross-Image Autoencoders
Kunjing Yang, Zhiwei Wang, Minru Bai
Image fusion aims to integrate structural and complementary information from multi-source images. However, existing fusion methods are often either highly task-specific, or general…
Spectral-Spatial Extraction through Layered Tensor Decomposition for Hyperspectral Anomaly Detection
Quan Yu, Yu-Hong Dai, Minru Bai
Low rank tensor representation (LRTR) methods are very useful for hyperspectral anomaly detection (HAD). To overcome the limitations that they often overlook spectral anomaly and r…
A Hybrid Registration and Fusion Method for Hyperspectral Super-resolution
Kunjing Yang, Minru Bai, TingLu
Fusing hyperspectral images (HSIs) with multispectral images (MSIs) has become a mainstream approach to enhance the spatial resolution of HSIs. Many HSI-MSI fusion methods have ach…
Efficient Low Rank Matrix Recovery With Flexible Group Sparse Regularization
Quan Yu, Minru Bai, Xinzhen Zhang
In this paper, we present a novel approach to the low rank matrix recovery (LRMR) problem by casting it as a group sparsity problem. Specifically, we propose a flexible group spars…