Dynamic 3D shape reconstruction under complex reflection and transmission conditions using multi-scale parallel single-pixel imaging

Depth measurement and three-dimensional (3D) imaging under complex reflection and transmission conditions are challenging and even impossible for traditional structured light techniques, owing to the precondition of pointto-point triangulation. Despite recent progress in addressing this problem, there is still no efficient and general solution. Herein, a Fourier dual-slice projection with depth-constrained localization is presented to separate and utilize different illumination and reflection components efficiently, which can significantly decrease the number of projection patterns in each sequence from thousands to fifteen. Subsequently, multi-scale parallel single-pixel imaging (MS-PSI) is proposed based on the established and proven position-invariant theorem, which breaks the local regional assumption and enables dynamic 3D reconstruction. Our methodology successfully unveils unseenbefore capabilities such as (1) accurate depth measurement under interreflection and subsurface scattering conditions, (2) dynamic measurement of the time-varying high-dynamic-range scene and through thin volumetric scattering media at a rate of 333 frames per second; (3) two-layer 3D imaging of the semitransparent surface and the object hidden behind it. The experimental results confirm that the proposed method paves the way for dynamic 3D reconstruction under complex optical field reflection and transmission conditions, benefiting imaging and sensing applications in advanced manufacturing, autonomous driving, and biomedical imaging.