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. Author manuscript; available in PMC: 2018 May 7.
Published in final edited form as: Phys Med Biol. 2017 Mar 22;62(9):3712–3734. doi: 10.1088/1361-6560/aa6869

Figure 2.

Figure 2

Flowchart illustrating the CMA-ES optimization of the motion estimation cost function. In each iteration, M candidate motion trajectories are sampled from a random distribution. For each candidate solution, the autofocus metric and the penalty term are computed (top and bottom branches of the flowchart) and added to yield a cost function value for that trajectory.