Eigenspace methods take advantage of the fact that a set of highly correlated images can be approximately represented by a small set of eigenimages. However, all known eigendecomposition algorithms are directly proportional to the resolution of original images. With the ability to generate consistently better resolution images using state-of-the-art equipment, these techniques still show performance issues and exponential increase in memory requirements. Also, these algorithms exploit one-dimensional temporal correlation between successive images and hence, cannot be efficiently applied to...