Fast algorithm for spectral mixture analysis of imaging spectrometer data

Imaging spectrometers acquire images in many narrow spectral bands but have limited spatial resolution. Spectral mixture analysis (SMA) is used to determine the fractions of the ground cover categories (the end-members) present in each pixel. In this paper a new iterative SMA method is presented and tested using a 30 band MAIS image. The time needed for each iteration is independent of the number of bands, thus the method can be used for spectrometers with a large number of bands. Further a new method, based on K-means clustering, for obtaining endmembers from image data is described and compared with existing methods. Using the developed methods the available MAIS image was analyzed using 2 to 6 endmembers.