Maximal-likelihood search improves the performance of the nearest neighbor method.
Proposed method is 2-10 faster than brute force, randomized kd-tree and perm-sort.
Unlike the baseline DEM, proposed method does not require quadratic memory space.
The method is applied with similarity measures which do not met metric properties.