Coded Illumination for 3D Lensless Imaging

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.

Lensless cameras provide novel designs for extreme imaging conditions that require small, thin form factor, large field-of-view, or large-area sensors [1], [2], [3], [4]. Compared to conventional lens-based cameras, lensless cameras are flat, thin, light-weight, and geometry flexible. Depth estimation with lensless imaging has been a challenging problem [3], [5], [6]. The primary reason is that the sensor responses for different depth planes have small differences, which makes the 3D reconstruction an ill-conditioned problem.