Compressive coding via random replicate mirror

Dung N. Tran, Luoluo Liu, Trac D. Tran, Sang Peter Chin, Jeffrey Korn, Eric T. Hoke

Abstract: We develop a Compressive Sensing (CS) imaging system that uses titled reflective sub-apertures placed at random angles to create replicates of random placement and orientation within the image plane and a variation adopting the beam splitter. We derive efficient methods based on sparse recovery to calibrate the transfer function of the camera from a set of calibrating images, which allows the reducing number of input-output pairs and to reconstruct the scene from random subsampled measurements after calibration. Various experiments are performed to illustrate successful camera calibration and scene reconstruction from sensor output.