  Mask-based lensless cameras offer a novel design for imaging systems by
replacing the lens in a conventional camera with a layer of coded mask. Each
pixel of the lensless camera encodes the information of the entire 3D scene.
Existing methods for 3D reconstruction from lensless measurements suffer from
poor spatial and depth resolution. This is partially due to the system ill
conditioning that arises because the point-spread functions (PSFs) from
different depth planes are very similar. In this paper, we propose to capture
multiple measurements of the scene under a sequence of coded illumination
patterns to improve the 3D image reconstruction quality. In addition, we put
the illumination source at a distance away from the camera. With such baseline
distance between the lensless camera and illumination source, the camera
observes a slice of the 3D volume, and the PSF of each depth plane becomes more
resolvable from each other. We present simulation results along with
experimental results with a camera prototype to demonstrate the effectiveness
of our approach.
