Singular value decomposition for approximate block matching in image coding

The minimum Euclidean distance matching of a 2-D image block can be reorganised, via singular value decomposition, into a set of computations with the block's singular vectors. The first two or three pairs of singular vectors are usually sufficient to achieve a good approximation, calculated with fewer operations than Euclidean matching. Full search motion estimation can be speeded up by at least a factor of 2, with minimal loss of accuracy.