A Layer-Based Restoration Framework for Variable-Aperture Photography

We present variable-aperture photography, a new method for analyzing sets of images captured with different aperture settings, with all other camera parameters fixed. We show that by casting the problem in an image restoration framework, we can simultaneously account for defocus, high dynamic range exposure (HDR), and noise, all of which are confounded according to aperture. Our formulation is based on a layered decomposition of the scene that models occlusion effects in detail. Recovering such a scene representation allows us to adjust the camera parameters in post-capture, to achieve changes in focus setting or depth-of-field with all results available in HDR. Our method is designed to work with very few input images: we demonstrate results from real sequences obtained using the three- image "aperture bracketing" mode found on consumer digital SLR cameras.