Computer vision tasks prefer the images focused at the related objects for a better performance, which requests a Auto-ReFocusing (ARF) function for using light field cameras. However, the current ARF schemes are time-consuming in practice, because they commonly need to render an image sequence for finding the optimally refocused frame. This paper presents an efficient ARF solution for light-field cameras based on modeling the refocusing point spread function (R-PSF). The R-PSF holds a simple linear relationship between refocusing depth and defocus blurriness. Such a linear relationship enables to determine the two candidates of the optimally refocused frame from only one initial refocused image. Because our method only involves three times of refocusing rendering for finding the optimally refocused frame, it is much more efficient than the current “rendering and selection” solutions which need to render a large number of refocused images.