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Physics-Guided Regime Unmixing

About

The Linear Mixing Model (LMM) dominates spectral unmixing for its simplicity, but fails under multiple scattering; existing nonlinear models compensate by applying a fixed regime uniformly across entire scenes. We propose Physics-Guided Regime Unmixing (PGRU), which estimates a pixel-wise scalar $\xi_i \in [0,1]$ from observable physical features to activate nonlinear mixing only where justified. Residuals from the Generalized Bilinear Model (GBM), the Post-Nonlinear Mixing Model (PPNM), and Hapke are combined via learned attention, yielding interpretable regime maps. Experiments on Samson, Jasper Ridge, and Urban show consistent improvements over baselines, with physical coherence $\rho > 0.90$.

Paula Pacheco, Pablo Granitto, Juan B. Cabral• 2026

Related benchmarks

TaskDatasetResultRank
Hyperspectral UnmixingJasper Ridge--
38
Hyperspectral Unmixing ReconstructionSamson
SAD0.052
4
Hyperspectral Unmixing ReconstructionUrban
SAD0.07
4
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