Manifold coordinate representations of hyperspectral imagery: Improvements in algorithm performance and computational efficiency

Abstract

Several years ago, NRL first demonstrated a computationally efficient framework for optimizing a set of intrinsic manifold coordinates for high-dimensional data such as hyperspectral imagery (HIS). Since that time, NRL has continued to improve the fidelity of the representation to describe the details of the nonlinear structure in even greater detail. In addition, working closely with CelesTech, several improvements have been made that increase the computational efficiency, accelerating processing speeds from hours to minutes.