3D Computational Ghost Imaging

TL;DR

This paper introduces a low-cost method for 3D imaging using computational ghost imaging with multiple single-pixel detectors, enabling 3D surface reconstruction from 2D images derived from different viewpoints.

Contribution

It extends computational ghost imaging to 3D surface reconstruction using multiple detectors and a single projector, overcoming previous 2D limitations.

Findings

Successfully reconstructed 3D surface of an object.

Compared results with stereo-photogrammetry showing comparable accuracy.

Demonstrated potential for low-cost, non-visible waveband 3D imaging.

Abstract

Computational ghost imaging retrieves the spatial information of a scene using a single pixel detector. By projecting a series of known random patterns and measuring the back reflected intensity for each one, it is possible to reconstruct a 2D image of the scene. In this work we overcome previous limitations of computational ghost imaging and capture the 3D spatial form of an object by using several single pixel detectors in different locations. From each detector we derive a 2D image of the object that appears to be illuminated from a different direction, using only a single digital projector as illumination. Comparing the shading of the images allows the surface gradient and hence the 3D form of the object to be reconstructed. We compare our result to that obtained from a stereo- photogrammetric system utilizing multiple high resolution cameras. Our low cost approach is compatible with consumer applications and can readily be extended to non-visible wavebands.