PS$^2$F: Polarized Spiral Point Spread Function for Single-Shot 3D Sensing
We propose a compact snapshot monocular depth estimation technique that relies on an engineered point spread function (PSF). Traditional approaches used in microscopic super-resolution imaging, such as the Double-Helix PSF (DHPSF), are ill-suited for scenes that are more complex than a sparse set of point light sources. We show, using the Cramér-Rao lower bound (CRLB), that separating the two lobes of the DHPSF and thereby capturing two separate images leads to a dramatic increase in depth accuracy. A unique property of the phase mask used for generating the DHPSF is that a separation of the phase mask into two halves leads to a spatial separation of the two lobes. We leverage this property to build a compact polarization-based optical setup, where we place two orthogonal linear polarizers on each half of the DHPSF phase mask and then capture the resulting image with a polarization sensitive camera. Results from simulations and a lab prototype demonstrate that our technique achieves up to $50\%$ lower depth error compared to state-of-the-art designs including the DHPSF, and the Tetrapod PSF, with little to no loss in spatial resolution.
PS2F: Polarized Spiral Point Spread Function for Single-Shot 3D Sensing Bhargav Ghanekar, Vishwanath Saragadam, Dushyant Mehra, Anna-Karin Gustavsson, Aswin C. Sankaranarayanan, Ashok Veeraraghavan Abstract—We propose a compact snapshot monocular depth estimation technique that relies on an engineered point spread function…
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