Blur Calibration for Depth from Defocus

Depth from defocus based methods rely on measuring the depth dependent blur at each pixel of the image. A core component in the defocus blur estimation process is the depth variant blur kernel. This blur kernel is often approximated as a Gaussian or pillbox kernel which only works well for small amount of blur. In general the blur kernel depends on the shape of the aperture and can vary a lot with depth. For more accurate blur estimation it is necessary to precisely model the blur kernel. In this paper we present a simple and accurate approach for performing blur kernel calibration for depth from defocus. We also show how to estimate the relative blur kernel from a pair of defocused blur kernels. Our proposed approach can estimate blurs ranging from small (single pixel) to sufficiently large (e.g. 77 x 77 in our experiments). We also experimentally demonstrate that our relative blur estimation method can recover blur kernels for complex asymmetric coded apertures which has not been shown before.