Quantum Hamiltonian Descent for Rigid Image Registration

Johannes David Voigts, Natacha Kuete Meli, Jan Lellmann

Keywords: image registration, quantum computing, optimization

TL;DR: Quantum computing approaches may help alleviate problems with non-convexity occuring in energy-based image registration.

Abstract: Energy-based formulations of the image registration problem are notoriously non-convex and traditionally require a combination of various techniques to obtain a good solution. In this work, we explore how a recent result from quantum computing can help with this task. Specifically, we show how to apply Quantum Hamiltonian Descent to the image registration problem. Numerical simulations on real-world data show that the method allows to recover good global minima despite the strong non-convexity, without relying on any heuristics or meta-strategies for aiding the optimization.

Primary Area: optimization

Submission Number: 9315