Adaptive compressed 3D imaging based on wavelet trees and Hadamard multiplexing with a single photon counting detector
This enables efficient high-resolution 3D imaging for applications requiring single-photon sensitivity and sub-ns temporal resolution, representing a strong specific gain in the domain.
The paper tackles the challenge of scaling photon counting 3D imaging to high spatial resolution by proposing a technique that uses wavelet trees and Hadamard multiplexing with a single-pixel detector, achieving acquisition and retrieval of a 512*512 pixel 3D image in as low as 17 seconds.
Photon counting 3D imaging allows to obtain 3D images with single-photon sensitivity and sub-ns temporal resolution. However, it is challenging to scale to high spatial resolution. In this work, we demonstrate a photon counting 3D imaging technique with short-pulsed structured illumination and a single-pixel photon counting detector. The proposed multi-resolution photon counting 3D imaging technique acquires a high-resolution 3D image from a coarse image and edges at successfully finer resolution sampled by Hadamard multiplexing along the wavelet trees. The detected power is significantly increased thanks to the Hadamard multiplexing. Both the required measurements and the reconstruction time can be significantly reduced by performing wavelet-tree-based regions of edges predication and Hadamard demultiplexing, which makes the proposed technique suitable for scenes with high spatial resolution. The experimental results indicate that a 3D image at resolution up to 512*512 pixels can be acquired and retrieved with practical time as low as 17 seconds.