Shape Recovery by Point Illumination using a Rotating Point Spread Function Imager

Shape Recovery for a three-dimensional (3D) extended object finds many applications. From imaging perspective, 3D extended objects can be modeled as consisting of densely packed point sources, each of which has its own independent brightness and depth parameter. Rotating point spread function (RPSF) imagers are capable to encode the depth of point sources, but the ability to decode that information for a crowded object becomes difficult. Here we present a novel technique that will allow for a robust reconstruction of the shape of an extended 3D object using point illumination via RPSF imager. Simulation results are obtained for obtaining depth map of extended objects using data frames with and without read noise.