Subspace estimates for real-time hyperspectral video systems

摘要

A method is presented for rapidly estimating the principal components used in dimension reduction for high frame rate hyperspectral video systems. Pixels entering and leaving a video frame are used to rapidly update the covariance matrix (:3;) and estimate the perturbed eigenpairs. Measuring the angle between the estimated dominant eigenspace and the exact eigenspace shows the method to be a good approximation when the difference between frames is low (;4;:3; :3;). This method reduces the time to calculate the principal components of high resolution hyperspectral video data by a factor of ~20.