  Depth from defocus and defocus deblurring from a single image are two
challenging problems that are derived from the finite depth of field in
conventional cameras. Coded aperture imaging is one of the techniques that is
used for improving the results of these two problems. Up to now, different
methods have been proposed for improving the results of either defocus
deblurring or depth estimation. In this paper, a multi-objective function is
proposed for evaluating and designing aperture patterns with the aim of
improving the results of both depth from defocus and defocus deblurring.
Pattern evaluation is performed by considering the scene illumination condition
and camera system specification. Based on the proposed criteria, a single
asymmetric pattern is designed that is used for restoring a sharp image and a
depth map from a single input. Since the designed pattern is asymmetric,
defocus objects on the two sides of the focal plane can be distinguished. Depth
estimation is performed by using a new algorithm, which is based on image
quality assessment criteria and can distinguish between blurred objects lying
in front or behind the focal plane. Extensive simulations as well as
experiments on a variety of real scenes are conducted to compare our aperture
with previously proposed ones.
