Fig. 2.

Optimal filters and defocus estimation. (A) The first six AMA filters. Filter energy is concentrated in a limited frequency range (shaded area). (B) Filter responses to amplitude spectra in the training set (1.25, 1.75, and 2.25 diopters not plotted). Symbols represent joint responses from the two most informative filters. Marginal distributions are shown on each axis. (C) Gaussian fits to filter responses. Thick lines are iso-likelihood contours on the maximum-likelihood surface determined from fits to the response distributions at trained defocus levels. Thin lines are iso-likelihood contours on interpolated response distributions (SI Methods). Circles indicate interpolated means separated by a d′ (i.e., Mahalanobis distance) of 1. Line segments show the direction of principle variance and ±1 SD. (D) Defocus estimates for test stimuli. Circles represent the mean defocus estimate for each defocus level. Error bars represent 68% (thick bars) and 90% (thin bars) confidence intervals. Boxes indicate defocus levels not in the training set. The equal-sized error bars at both trained and untrained levels indicates that the algorithm outputs continuous estimates.