Spectral mixture analysis of hyperspectral data using Genetic Algorithm and Spectral Angle Constraint (GA-SAC)

Abstract

A Genetic Algorithm and Spectral Angle Constraint (GA-SAC) abundance estimation method is presented to improve the accuracy of abundance maps affected by illumination effects and sensor noise. As an improved version of the Spectral Angle Constraint (SAC), the GA-SAC was compared against several existing techniques. Preliminary results showed advantages of the proposed GA-SAC method from tests involving a simulated hyperspectral data set as well as for mapping mineral abundances using AVIRIS data over Cuprite, Nevada.