Micron scale 3D imaging with a multi-camera array

We present a novel approach for capturing gigapixel-resolution micron-scale three-dimensional (3D) images of large complex macroscopic objects using a 9 6 multi-camera array paired with a custom 3D reconstruction algorithm.Our system overcomes inherent trade-offs among resolution, field of view (FOV), and depth of field (DOF) by capturing stereoscopic focal stacks across multiple perspectives, enabling an effective FOV of approximately 135 128 degrees and capturing surface depth maps at lateral resolutions less than 40 m and depth resolutions of about 0.5 mm.To achieve all-in-focus RGB (red, green, and blue) composites with precise depth, we employ a novel self-supervised neural network that integrates focus and stereo cues, resulting in highly accurate 3D reconstructions robust to variations in lighting and surface reflectance.We validate the proposed approach by scanning 3D objects, including those with known 3D geometries, and demonstrate sub-millimeter depth accuracy across a variety of scanned objects.This represents a powerful tool for digitizing large complex forms, allowing for near-microscopic details in both depth mapping and high-resolution image reconstruction.