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Power-Balanced Hybrid Optics Boosted Design for Achromatic Extended-Depth-of-Field Imaging via Optimized Mixed OTF

arXiv 2103.05720 ↗First posted 9 Mar 2021physics.optics eess.IVcited by 1

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Abstract (arXiv)

The power-balanced hybrid optical imaging system is a special design of a diffractive computational camera, introduced in this paper, with image formation by a refractive lens and Multilevel Phase Mask (MPM). This system provides a long focal depth with low chromatic aberrations thanks to MPM and a high energy light concentration due to the refractive lens. We introduce the concept of optical power balance between the lens and MPM which controls the contribution of each element to modulate the incoming light. Additional unique features of our MPM design are the inclusion of quantization of the MPM's shape on the number of levels and the Fresnel order (thickness) using a smoothing function. To optimize optical power-balance as well as the MPM, we build a fully-differentiable image formation model for joint optimization of optical and imaging parameters for the proposed camera using Neural Network techniques. Additionally, we optimize a single Wiener-like optical transfer function (OTF) invariant to depth to reconstruct a sharp image. We numerically and experimentally compare the designed system with its counterparts, lensless and just-lens optical systems, for the visible wavelength interval (400-700)nm and the depth-of-field range (0.5-∞m for numerical and 0.5-2m for experimental). The attained results demonstrate that the proposed system equipped with the optimal OTF overcomes its counterparts (even when they are used with optimized OTF) in terms of reconstruction quality for off-focus distances. The simulation results also reveal that optimizing the optical power-balance, Fresnel order, and the number of levels parameters are essential for system performance attaining an improvement of up to 5dB of PSNR using the optimized OTF compared with its counterpart lensless setup.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 9 Mar 2021.

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