High-resolution ghost imaging through complex scattering media via a temporal correction

High-resolution ghost imaging through complex scattering media via a temporal correction: erratum

We correct a typographical error in our Letter [Opt. Lett.47, 3692 (2022)10.1364/OL.463897]. The corrections have no influence on the results and conclusions of the original Letter.

A dual-modality optical system for single-pixel imaging and transmission through scattering media

It is well recognized that it is difficult to develop an optical system to retrieve effective information when dynamic and turbid water exists in an optical channel. It could be more challenging to incorporate dual or multiple modalities in one optical system. In this Letter, we report a dual-modality optical system for single-pixel imaging (SPI) and transmission through scattering media. A series of mutually-orthogonal random illumination patterns are designed and adopted to realize high-resolution image recovery in SPI. The data to be transmitted are also encoded into random illumination patterns in a differential way, and high-fidelity free-space optical data transmission can be simultaneously realized. Experimental results validate feasibility of the proposed optical system and its high robustness against scattering. The developed dual-modality optical system realizes high-resolution SPI and high-fidelity data transmission in scattering media using only one set of realizations, offering an efficient implementation with reduced power and equipment requirements. The proposed method is promising toward the development of an integrated system with multiple modalities for optical information retrieval, especially in dynamic scattering media.

Measurement Modeling and Performance Analysis of a Bionic Polarimetric Imaging Navigation Sensor Using Rayleigh Scattering to Generate Scattered Sunlight

The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement performance analysis method of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the overall measurement performance of BPINS are investigated, and the Stokes vector-based measurement error model of BPINS is introduced. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed using Rayleigh scattering to generate scattered sunlight as a known incident light source. The numerical results show that in angle of E-vector (AoE) measurement, the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation; in degree of linear polarization (DoLP) measurement, the grayscale response inconsistency of CMOS has a more significant impact. This finding can accurately guide the subsequent calibration of BPINS, and the quantitative results provide an important theoretical reference for its optimal design.

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.

High-fidelity and high-robustness free-space ghost transmission in complex media with coherent light source using physics-driven untrained neural network

It is well recognized that it is challenging to realize high-fidelity and high-robustness ghost transmission through complex media in free space using coherent light source. In this paper, we report a new method to realize high-fidelity and high-robustness ghost transmission through complex media by generating random amplitude-only patterns as 2D information carriers using physics-driven untrained neural network (UNN). The random patterns are generated to encode analog signals (i.e., ghost) without any training datasets and labeled data, and are used as information carriers in a free-space optical channel. Coherent light source modulated by the random patterns propagates through complex media, and a single-pixel detector is utilized to collect light intensities at the receiving end. A series of optical experiments have been conducted to verify the proposed approach. Experimental results demonstrate that the proposed method can realize high-fidelity and high-robustness analog-signal (ghost) transmission in complex environments, e.g., around a corner, or dynamic and turbid water. The proposed approach using the designed physics-driven UNN could open an avenue for high-fidelity free-space ghost transmission through complex media.

Learning-based correction with Gaussian constraints for ghost imaging through dynamic scattering media

In this Letter, we propose a learning-based correction method to realize ghost imaging (GI) through dynamic scattering media using deep neural networks with Gaussian constraints. The proposed method learns the wave-scattering mechanism in dynamic scattering environments and rectifies physically existing dynamic scaling factors in the optical channel. The corrected realizations obey a Gaussian distribution and can be used to recover high-quality ghost images. Experimental results demonstrate effectiveness and robustness of the proposed learning-based correction method when imaging through dynamic scattering media is conducted. In addition, only the half number of realizations is needed in dynamic scattering environments, compared with that used in the temporally corrected GI method. The proposed scheme provides a novel, to the best of our knowledge, insight into GI and could be a promising and powerful tool for optical imaging through dynamic scattering media.

High-quality and high-diversity conditionally generative ghost imaging based on denoising diffusion probabilistic model

Deep-learning (DL) methods have gained significant attention in ghost imaging (GI) as promising approaches to attain high-quality reconstructions with limited sampling rates. However, existing DL-based GI methods primarily emphasize pixel-level loss and one-to-one mapping from bucket signals or low-quality GI images to high-quality images, tending to overlook the diversity in image reconstruction. Interpreting image reconstruction from the perspective of conditional probability, we propose the utilization of the denoising diffusion probabilistic model (DDPM) framework to address this challenge. Our designed method, known as DDPMGI, can not only achieve better quality but also generate reconstruction results with high diversity. At a sampling rate of 10%, our method achieves an average PSNR of 21.19 dB and an SSIM of 0.64, surpassing the performance of other comparison methods. The results of physical experiments further validate the effectiveness of our approach in real-world scenarios. Furthermore, we explore the potential application of our method in color GI reconstruction, where the average PSNR and SSIM reach 20.055 dB and 0.723, respectively. These results highlight the significant advancements and potential of our method in achieving high-quality image reconstructions in GI, including color image reconstruction.

High-resolution self-corrected single-pixel imaging through dynamic and complex scattering media

Imaging with single-pixel detectors becomes attractive in many applications where pixelated detectors are not available or cannot work. Based on a correlation between the probing patterns and the realizations, optical imaging with single-pixel detector offers an indirect way to recover a sample. It is well recognized that single-pixel optical imaging through dynamic and complex scattering media is challenging, and dynamic scaling factors lead to serious mismatches between the probing patterns and the realizations. In this paper, we report self-corrected imaging to realize high-resolution object reconstruction through dynamic and complex scattering media using a parallel detection with dual single-pixel detectors. The proposed method can supervise and self-correct dynamic scaling factors, and can implement high-resolution object reconstruction through dynamic and complex scattering media where conventional methods could not work. Spatial resolution of 44.19 µm is achieved which approaches diffraction limit (40.0 µm) in the designed optical setup. The achievable spatial resolution is dependent on pixel size of spatial light modulator. It is experimentally validated that the proposed method shows unprecedented robustness against complex scattering. The proposed self-corrected imaging provides a solution for ghost recovery, enabling high-resolution object reconstruction in complex scattering environments.

Target Velocity Ghost Imaging Using Slice Difference Method

Ghost imaging is a technique that uses the correlation between reference and signal arms to obtain intensity images of targets. Compared with the existing laser active imaging methods, ghost imaging can improve the signal-to-noise ratio and resolution. In this paper, through the use of the slice difference method, we propose a new scheme that allows a velocity image of moving targets to be obtained. We conduct a complete theoretical analysis and provide a proof-of-principle experiment. The experimental results are in good agreement with those of the theoretical analysis, and a velocity image with 64 × 64 resolution is obtained. This protocol achieves a great increase in the signal-to-noise ratio over what would be achievable using direct imaging. The results show a fully functional instance of velocity imaging, which is a key advancement on the path towards the multi-dimensional information acquisition of moving targets. Our scheme fulfils an urgent need for the detection of moving targets and may thus find use in fields such as target attitude perception and security monitoring.