In this paper, the new algorithm based on clustered multitask network is
proposed to solve spectral unmixing problem in hyperspectral imagery. In the
proposed algorithm, the clustered network is employed. Each pixel in the
hyperspectral image considered as a node in this network. The nodes in the
network are clustered using the fuzzy c-means clustering method. Diffusion
least mean square strategy has been used to optimize the proposed cost
function. To evaluate the proposed method, experiments are conducted on
synthetic and real datasets. Simulation results based on spectral angle
distance, abundance angle distance and reconstruction error metrics illustrate
the advantage of the proposed algorithm compared with other methods.Comment: one column, 22 pages, 12 figures, journal. arXiv admin note:
substantial text overlap with arXiv:1902.07593, arXiv:1812.1078
