Deep Generative Models for Library Augmentation in Multiple Endmember Spectral Mixture Analysis

20 Sep 2019Ricardo Augusto BorsoiTales ImbiribaJosé Carlos Moreira BermudezCédric Richard

Multiple Endmember Spectral Mixture Analysis (MESMA) is one of the leading approaches to perform spectral unmixing (SU) considering variability of the endmembers (EMs). It represents each EM in the image using libraries of spectral signatures acquired a priori... (read more)

PDF Abstract


No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.