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 ξi∈[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 ρ>0.90.
@article{arxiv.2605.04247,
title = {Physics-Guided Regime Unmixing},
author = {Paula Pacheco and Pablo Granitto and Juan B. Cabral},
journal= {arXiv preprint arXiv:2605.04247},
year = {2026}
}