Category decomposition based on maximum likelihood estimation.
Masao Matsumoto, Kouki FUJIKU, Kiyoshi Tsuchiya, Kohei Arai · Journal of the Japan society of photogrammetry and remote sensing · 1991
To make the accurate retrieval of the statistically meaningful proportion of each category among MIXEL's, a category decomposition method based on maximum likelihood estimation is proposed .In this method, the observed multispectral vector is considered as a probability variable along with the approximation that each pure pixel value is characterized by normal distribution.The results show that this method can retrieve more accurate proportion than previous method.And 2 indices that estimate the degree of error are proposed .The first one is always available to show the degree of estimation error in each category , and the second one is not always available to estimate the degree of estimation error of each MIXEL .1.