A technique to construct an affine invariant descriptor for remote-sensing image registration based on the scale invariant features transform （SIFT） in a kernel space is proposed. Affine invariant SIFT descriptor is first developed in an elliptical region determined by the Hessian matrix of the feature points. Thereafter, the descriptor is mapped to a feature space induced by a kernel, and a new descriptor is constructed by whitening the mapped descriptor in the feature space, with the transform called KW-SIFT. In a final step, the new descriptor is used to register remote-sensing images. Experimental results for remote-sensing image registration indicate that the proposed method improves the registration performance as compared with other related methods.
