Single-pixel 3D imaging based on fusion temporal data of single photon detector and millimeter-wave radar
This addresses a specific issue in low-cost 3D imaging for applications requiring clear reconstructions, but it is incremental as it builds on existing single-pixel techniques.
The paper tackled the problem of symmetry blur in single-pixel 3D imaging by proposing a fusion method using single-photon detector and millimeter-wave radar temporal data, which effectively eliminated the blur and improved image quality as demonstrated in simulations and experiments.
Recently, there has been increased attention towards 3D imaging using single-pixel single-photon detection (also known as temporal data) due to its potential advantages in terms of cost and power efficiency. However, to eliminate the symmetry blur in the reconstructed images, a fixed background is required. This paper proposes a fusion-data-based 3D imaging method that utilizes a single-pixel single-photon detector and a millimeter-wave radar to capture temporal histograms of a scene from multiple perspectives. Subsequently, the 3D information can be reconstructed from the one-dimensional fusion temporal data by using Artificial Neural Network (ANN). Both the simulation and experimental results demonstrate that our fusion method effectively eliminates symmetry blur and improves the quality of the reconstructed images.