1. A method for reducing dimensionality of a hyperspectral image in multiple passes, comprising: receiving an initial basis vector set that includes a plurality of members for a hyperspectral image having a plurality of pixels, wherein the initial set of basis vectors corresponds to a reduced data set for the hyperspectral image; segregating a plurality of pixels in the reduced data set for the hyperspectral image into anomalous pixels and common pixels based on the initial basis vector set; and generating a basis vector set for the common pixels to re-reduce the data set for the hyperspectral image, wherein the re-reduced data set for the hyperspectral image includes the basis vector set generated for the common pixels and an unreduced data set for the anomalous pixels in the reduced data set.