Abstract
The majority of the existing unmixing methods use a unique set of endmembers for spectral mixture analysis of the entire image, failing to account that each pixel may be comprised of a different combination of endmembers. Multiple endmember spectral mixture analysis (MESMA) allows the number and types of endmembers to vary on a per-pixel basis. The existing MESMA algorithms have high computational cost. In this paper, a novel MESMA is introduced, called MESMA-SAD, which aims to minimize the time-processing by combining the Spectral Angle Distance (SAD) values and the mean absolute errors (MAE). In order to evaluate the proposed method, an AVIRIS hyperspectral data has been used.
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