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The power-balanced hybrid optical imaging system is a special design of adiffractive computational camera, introduced in this paper, with imageformation by a refractive lens and Multilevel Phase Mask (MPM). This systemprovides a long focal depth with low chromatic aberrations thanks to MPM and ahigh energy light concentration due to the refractive lens. We introduce theconcept of optical power balance between the lens and MPM which controls thecontribution of each element to modulate the incoming light. Additional uniquefeatures of our MPM design are the inclusion of quantization of the MPM's shapeon the number of levels and the Fresnel order (thickness) using a smoothingfunction. To optimize optical power-balance as well as the MPM, we build afully-differentiable image formation model for joint optimization of opticaland 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 andexperimentally compare the designed system with its counterparts, lensless andjust-lens optical systems, for the visible wavelength interval (400-700)nm andthe depth-of-field range (0.5-$\infty$m for numerical and 0.5-2m forexperimental). The attained results demonstrate that the proposed systemequipped with the optimal OTF overcomes its counterparts (even when they areused with optimized OTF) in terms of reconstruction quality for off-focusdistances. The simulation results also reveal that optimizing the opticalpower-balance, Fresnel order, and the number of levels parameters are essentialfor system performance attaining an improvement of up to 5dB of PSNR using theoptimized OTF compared with its counterpart lensless setup.

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