  In the past few decades, there has been intensive research concerning the
Unmixing of hyperspectral images. Some methods such as NMF, VCA, and N-FINDR
have become standards since they show robustness in dealing with the unmixing
of hyperspectral images. However, the research concerning the unmixing of
multispectral images is relatively scarce. Thus, we extend some unmixing
methods to the multispectral images. In this paper, we have created two
simulated multispectral datasets from two hyperspectral datasets whose ground
truths are given. Then we apply the unmixing methods (VCA, NMF, N-FINDR) to
these two datasets. By comparing and analyzing the results, we have been able
to demonstrate some interesting results for the utilization of VCA, NMF, and
N-FINDR with multispectral datasets. Besides, this also demonstrates the
possibilities in extending these unmixing methods to the field of multispectral
imaging.
