Fast Alignment of Digital Images Using a Lower Bound on an Entropy Metric (TP-L5)

Author(s) : Mert Sabuncu (Princeton University, USA) Peter Ramadge (Princeton University, USA)

Abstract : We propose a registration algorithm based on successively refined quantization and an alignment metric derived from an minimal spanning tree entropy estimate. The metric favors edge alignment, is fast to compute, and compares well in experiments with competing approaches.

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