A practical method for constructing the mixture model for a spectral class

Remotely sensed multispectral image data are found in grouped form with (say) s spectral components (bands). In this study, a practical method for constructing a mixture model or the probability density function of the mixture of k (3 less than or equal to k less than or equal to s) normal distributions for a spectral class is given. A new method for estimation of the mixing proportions of spectral components (bands) in the remotely sensed multispectral image data is proposed with the assumption that the spectral component (band) means are different from each other.