Separable Coded Aperture for Depth from a Single Image

Abstract

We propose the use of a separable coded aperture to estimate depth from a single defocused image, and derive a criterion for evaluating aperture patterns with respect to depth discrimination. With a separable coded aperture, two-dimensional (2D) point spread functions (PSFs) are separated into the product of horizontal and vertical one-dimensional (1D) PSFs. Depth is recovered by finding the scale of the 1D PSFs at each pixels based on the space-frequency analysis. Benefiting from 1D PSFs and the optimal code, our approach obtains more accurate depth especially on depth boundaries, and is faster since 2D computation is reduced to 1D. Experimental results on synthetic and real-captured data demonstrates the effectiveness of our approach.