Figure 9.

The value of the cost function (i.e. entropy) as a function of the iteration number. (a) The iterations for the experiment given in Fig. 4 (subject 1) and (b) Fig. 6 (subject 2) are shown. For the case with multiple in-plane rotations, the convergence of method 2 was faster than method 1 (a) due to the lower number of unknowns. For the case with more complicated motion where the subject performed both shaking and nodding, it was observed that the segmentation based autofocusing did not converge during 200 iterations to yield adequate image quality (b). This was due to the high number of segments, and thus, the high number of unknowns (Fig. 6d). However, cross-calibration matrix based autofocusing had a fast convergence rate in this case. Given 200 iterations, the total computation time was around 2 hours.