Comments on "comparison between orthogonal subspace projection and background subtraction techniques applied to remote-sensing data"

Ben-David and Ren Appl. Opt. 44, 3846 (2005)] discussed methods of estimating the concentration of chemical vapor plumes in hyperspectral images. The authors of that paper concluded that a technique called orthogonal subspace projection (OSP) produces better concentration estimates than background subtraction when certain stochastic noise conditions are present in the data. While that conclusion is correct, it is worth noting that the data can be whitened to improve the performance of the background subtraction method. In particular, if the noise is multivariate Gaussian, then whitening will ensure that the background subtraction method is superior to OSP.