Hyperspectral image classification requires a compact representation that can jointly capture discriminative spectral cues, local spatial structures, and efficient inference behavior under limited annotations. Existing CNN-based methods provide effective local pattern extraction but are less capable of modeling long-ra...
Xiao-Fei Yang, Rui-Ying Zhang, Wei-Jia Cao et al.· IEEE Transactions on Geoscie...· 0 citations
Multiplicative noise poses a challenge in coherent and signal-dependent imaging owing to its intensity-dependent variance and frequently non-Gaussian distribution. We propose a deterministic nonlocal estimator that combines a logarithmic Yeo--Johnson transformation, patch grouping, an adaptive singular basis, and spars...
Xuran Hu, Mingzhe Zhu, Djordje Stanković et al.· 0 citations
Hyperspectral image classification (HSIC) relies on effective modeling of coupled spectral–spatial interactions. While recent CNN-, Transformer-, and Mamba-based methods have improved feature extraction, most of them organize token interaction through layerwise aggregation and repeated stacking, leaving cross-layer pro...
Zihang Luo, Xiao-Fei Yang, Fei Yu et al.· IEEE Transactions on Geoscie...· 0 citations
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