Projection-based methods for hyperspectral image fraction estimation

In this paper, we investigate the issues that arise with the use of large spectral libraries in practical applications of fraction estimation in hyperspectral imaging. We then present a new technique for fraction estimation based on the method of successive projections onto convex sets. Results are presented that demonstrate the ability of this technique to recover information that cannot be recovered using traditional techniques based on linear regression alone.