Development of raw-image ray-bundling for focused and unfocused plenoptic 3D-PTV

Abstract

This paper introduces a new plenoptic 3D particle tracking velocimetry (3D-PTV) technique called raw-image ray-bundling (RIRB), which combines the 3D clustering algorithm of light-field ray-bundling (LFRB) with the raw image segmentation concept of epipolar triangular connectivity (ETC). The combined approach provides flexibility towards accommodating both unfocused and focused plenoptic cameras. Additionally, the RIRB algorithm bypasses the computational step of perspective-view generation in LFRB, thereby allowing lower specification microlens arrays (MLA) to be used without excessive loss of measurement resolution. As part of RIRB’s development, synthetic particle-field data and experimental dot-panel targets were used to demonstrate the viability of RIRB. The latter was performed through a VEO640 high-speed camera retrofitted for plenoptic imaging with a 2.5 mm focal-length, F/10 MLA. For the synthetic dataset, RIRB demonstrated better performance than LFRB in processing low-resolution images, with mean errors below 0.85% of the field-of-view (FOV). Additionally, a synthetic Hagen-Poiseuille flow dataset was used to demonstrate the feasibility of RIRB for 3D flow velocimetry using both high and low-resolution images. For the experimental dataset, x/y errors below 0.15% of the FOV and z error below 1.0% were achieved. The combination of synthetic and experimental validations suggests RIRB is a promising approach for 3D triangulation from both focused and unfocused raw plenoptic images, overcoming the low-resolution issue inherent with perspective-view decoding in plenoptic systems.