Abstract

Single-image depth from defocus is limited by blur-radius ambiguity: two object distances on different sides of the focal plane can produce similar point spread functions (PSFs). We study single-shot dual-focus imaging (DFI) with a polarizer-free liquid crystal (LC) lens, where the ordinary-ray component remains unmodulated while the extraordinary-ray component is refocused. Unlike conventional multi-capture DFD, the proposed system records a dual-focus superposition in one exposure and selects the optical setting before network training using the ambiguity-interval length A and PSF correlation Cr. We show that DFI does not reduce ambiguity unconditionally: its benefit depends on the LC-lens power. A deblurring-based depth estimation network with a physics-calibrated Wiener bank translates the selected dual-focus cue into quantitative depth. On model-matched synthetic DFI data with an 8 m focus setting, the proposed configuration reduces RMS error from 0.227±0.001 m to 0.190±0.001 m (mean ± s.d. over four independent runs) relative to single-focus imaging. A 116-pair indoor prototype dataset provides feasibility evidence under the tested configuration, but is not used to claim broad physical generalization.

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