Spectral unmixing using linear unmixing under spatial autocorrelation constraints

This paper presents a spectral unmixing approach that is implemented using linear unminxing method by a genetic algorithm. The unmixing is constrained not only by the negativity and sum-to-one of the abundances of endmembers at each pixel but also by the spatial autocorrelation of their abundances among eight neighbor pixels. The Moran´s I indices are proposed to describe the spatial autocorrelation among a pixel and its neighborhood. Based on the above constraints, the objective of unmixing by genetic algorithm is to minimize the mean square error of mixed spectral values. We tested this approach using Chinese HJ-satellite images and obtained an acceptable result.