Spectral unmixing (SU) is a significant preprocessing task for handling hyperspectral images (HSI), but its process affected by nonlinearity and spectral variability (SV). Currently, SV considered within the framework of linear mixing models (LMM), which ignores nonlinear effects in scene. To address that issue, we consider on SU while investigating images. Furthermore, an augmented generalized...

Due to the complex interaction of light with mixed materials, reflectance spectra are highly nonlinearly related pure material endmember spectra, making it hard estimate fractional abundances materials. Changing illumination conditions and cross-sensor situations cause spectral variability, further complicating unmixing procedure. In this work, we propose a supervised approach unmix mineral pow...