Enhancement of high spectral resolution remote-sensing data by a noise-adjusted principal components transform

High-spectral-resolution remote-sensing data are first transformed so that the noise covariance matrix becomes the identity matrix. Then the principal components transform is applied. This transform is equivalent to the maximum noise fraction transform and is optimal in the sense that it maximizes t... View More