What does BEAE mean in ACADEMIC & SCIENCE

BEAE stands for Blind End-member and Abundance Estimation. It is a type of spectral unmixing method used to identify the dominant components of a mixed signal.

BEAE attempts to estimate the abundance of the components present in a signal while also attempting to identify the endmembers, or basic constituents that make up the signal.

Unlike other types of spectral unmixing methods, which rely on known endmember spectra for identification, BEAE works using only data obtained from within the mixed signal itself. This makes it ideal for situations where prior knowledge about endmembers is unavailable or uncertain.

One potential limitation with using BEAE is that it can require more computation time compared to other methods since it has access only to limited information within each mixed pixel. Additionally, due to its blind approach, there is rarely an ability to “verify” endmember results as one would have with other approaches such as traditional least squares linear unmixing (LSU).

BEAE can be used in scenarios where prior knowledge about endmembers or abundances are unknown or uncertain and manual intervention must be minimized. Its lack of reliance on prior knowledge makes it useful when dealing with nonlinearities in data or when analyzing large datasets over multiple scales.