Underwater ghost imaging with detection distance up to 9.3 attenuation lengths.

Underwater ghost imaging LiDAR is an effective method of underwater detection. In this research, theoretical and experimental investigations were conducted on underwater ghost imaging, combining the underwater optical field transmission model with the inherent optical parameters of a water body. In addition, the Wells model and the approximate Sahu-Shanmugam scattering phase function were used to create a model for underwater optical transmission. The second-order Glauber function of the optical field was then employed to analyze the scattering field degradation during the transmission process. The simulation and experimental results verified that the proposed underwater model could better reveal the degrading effect of a water body on ghost imaging. A further series of experiments comparing underwater ghost imaging at different detection distances was also conducted. In the experimental system, gated photomultiplier tube (PMT) was used to filter out the peak of backscattering, allowing a larger gain to be set for longer-range detection of the target. The laser with a central wavelength of 532 nm was operated at a frequency of 2 KHz, with a single pulse energy of 2 mJ, a pulse width of 10 ns. High-reflective targets were imaged up to 65.2 m (9.3 attenuation lengths (ALs), attenuation coefficient c = 0.1426 m-1, and scattering coefficient b = 0.052 m-1) and diffuse-reflection targets up to 41.2 m (6.4 ALs, c = 0.1569 m-1, and b = 0.081 m-1). For the Jerlov-I (c = 0.048 m-1 and b = 0.002 m-1) water body, the experimentally obtained maximum detection distance of 9.3 ALs can be equivalent to 193.7 m under the same optical system conditions.

Experimental investigation of chirped amplitude modulation heterodyne ghost imaging.

We have constructed a chirped amplitude modulation heterodyne ghost imaging (CAM-HGI) experimental system that demonstrates a robust ability against background light in experiments. In the experiments, the background light is simulated by irradiating a spatiotemporal random modulated light field onto the target. The effects of background light, modulation depth and modulation duration of the signal light source on CAM-HGI are investigated experimentally. The results show that the quality of CAM-HGI can be improved by increasing the modulation depth and the modulation duration of the signal light source, and more importantly, an image with a good signal-to-noise ratio (SNR) can be achieved even when the irradiation SNR is lower than -30 dB. This technique of CAM-HGI has an important application prospect for laser imaging in strong background light environments.

Focal-plane three-dimensional imaging method based on temporal ghost imaging: a proof of concept simulation.

A new focal-plane three-dimensional (3D) imaging method based on temporal ghost imaging is proposed and demonstrated. By exploiting the advantages of temporal ghost imaging, this method enables the utilization of slow integrating cameras and facilitates 3D surface imaging within the framework of sequential flood-illumination and focal-plane detection. The depth information is achieved by a temporal correlation between received and reference signals with multiple-shot, and the reflectivity information is achieved by flash imaging with a single-shot. The feasibility and performance of this focal-plane 3D imaging method have been verified through theoretical analysis and numerical experiments.

Experimental investigation of the quality of ghost imaging via sparsity constraints.

Sampling number and detection signal-to-noise ratio (SNR) are two major factors influencing imaging quality. Combining the image's sparsity in the representation basis with the ghost imaging (GI) approach, GI via sparsity constraints (GISC) can nonlocally image the object even when the measurement number is far fewer than the Nyquist criteria required for the conventional GI reconstruction algorithm. The influence of receiving the system's numerical aperture and detection SNR in the test path to GISC is studied through experiments. It is also shown that the quality of GISC depends on the object's sparse representation basis.