Endmember Detection using Enhanced Constrained Optimization in Hyperspectral Imaging

A new algorithm is presented for linear spectral mixture analysis that respects the constraints on the endmembers. The results show that it provides a more robust solution as compared to the ICE and SPICE algorithms due to the use of constrained quadratic optimization for endmember detection.