TY - JFULL AU - Mahamed G.H. Omran and Andries P Engelbrecht and Ayed Salman PY - 2008/7/ TI - A PSO-based End-Member Selection Method for Spectral Unmixing of Multispectral Satellite Images T2 - International Journal of Computer and Information Engineering SP - 2231 EP - 2240 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/7090 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 18, 2008 N2 - An end-member selection method for spectral unmixing that is based on Particle Swarm Optimization (PSO) is developed in this paper. The algorithm uses the K-means clustering algorithm and a method of dynamic selection of end-members subsets to find the appropriate set of end-members for a given set of multispectral images. The proposed algorithm has been successfully applied to test image sets from various platforms such as LANDSAT 5 MSS and NOAA's AVHRR. The experimental results of the proposed algorithm are encouraging. The influence of different values of the algorithm control parameters on performance is studied. Furthermore, the performance of different versions of PSO is also investigated. ER -