High-performance scanning-mode polarization based computational ghost imaging (SPCGI)

Polarization motivating high-performance weak targets' imaging based on a dual-discriminator GAN

High-level detection of weak targets under bright light has always been an important yet challenging task. In this paper, a method of effectively fusing intensity and polarization information has been proposed to tackle this issue. Specifically, an attention-guided dual-discriminator generative adversarial network (GAN) has been designed for image fusion of these two sources, in which the fusion results can maintain rich background information in intensity images while significantly completing target information from polarization images. The framework consists of a generator and two discriminators, which retain the texture and salient information as much as possible from the source images. Furthermore, attention mechanism is introduced to focus on contextual semantic information and enhance long-term dependency. For preserving salient information, a suitable loss function has been introduced to constrain the pixel-level distribution between the result and the original image. Moreover, the real scene dataset of weak targets under bright light has been built and the effects of fusion between polarization and intensity information on different weak targets have been investigated and discussed. The results demonstrate that the proposed method outperforms other methods both in subjective evaluations and objective indexes, which prove the effectiveness of achieving accurate detection of weak targets in bright light background.

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.

Optical authentication method based on correspondence ghost imaging

Ghost imaging technology has a great application potential in optical security because of its non-local characteristics. In this paper, on the basis of computational ghost imaging, an optical authentication scheme is proposed that utilizes the correspondence imaging technique for the preliminary reconstruction of the object image, and then authenticates the image by a nonlinear correlation algorithm. Different from the previous optical authentication schemes that usually adopted random selection of measurements, this authentication method consciously selects the bucket detector measurement values with large fluctuation and can achieve authentication using ultra-low data volumes less than 1% of the Nyquist limit. In brief, this scheme is easy to implement and has a simpler algorithm and higher stability, which is a tremendous advantage in practical optical authentication systems. The simulation and physical experimental results demonstrate the feasibility of the scheme.

Optimized sinusoidal patterns for high-performance computational ghost imaging

Computational ghost imaging (CGI) can reconstruct scene images by two-order correlation between sampling patterns and detected intensities from a bucket detector. By increasing the sampling rates (SRs), imaging quality of CGI can be improved, but it will result in an increasing imaging time. Herein, in order to achieve high-quality CGI under an insufficient SR, we propose two types of novel sampling methods for CGI, to the best of our knowledge, cyclic sinusoidal-pattern-based CGI (CSP-CGI) and half-cyclic sinusoidal-pattern-based CGI (HCSP-CGI), in which CSP-CGI is realized by optimizing the ordered sinusoidal patterns through "cyclic sampling patterns," and HCSP-CGI just uses half of the sinusoidal pattern types of CSP-CGI. Target information mainly exists in the low-frequency region, and high-quality target scenes can be recovered even at an extreme SR of 5%. The proposed methods can significantly reduce the sampling number and real-time ghost imaging possible. The experiments demonstrate the superiority of our method over state-of-the-art methods both qualitatively and quantitatively.

Self-attention module in a multi-scale improved U-net (SAM-MIU-net) motivating high-performance polarization scattering imaging

Polarization imaging has outstanding advantages in the field of scattering imaging, which still encounters great challenges in heavy scattering media systems even though there are helps from deep learning technology. In this paper, we propose a self-attention module (SAM) in multi-scale improved U-net (SAM-MIU-net) for the polarization scattering imaging, which can extract a new combination of multidimensional information from targets effectively. The proposed SAM-MIU-net can focus on the stable feature carried by polarization characteristics of the target, so as to enhance the expression of the available features, and make it easier to extract polarization features which help to recover the detail of targets for the polarization scattering imaging. Meanwhile, the SAM's effectiveness has been verified in a series of experiments. Based on proposed SAM-MIU-net, we have investigated the generalization abilities for the targets' structures and materials, and the imaging distances between the targets and the ground glass. Experimental results demonstrate that our proposed SAM-MIU-net can achieve high-precision reconstruction of target information under incoherent light conditions for the polarization scattering imaging.

Detection and imaging of distant targets by near-infrared polarization single-pixel lidar

Single-pixel imaging (SPI) is a new technology with many applications and prospects. Polarization detection technology can improve the detection and identification ability of the imaging system. A near-infrared polarization SPI lidar system is designed to realize detection and polarization imaging of outdoor long-range targets. The depth, intensity, linear polarization, and polarization degree images of typical remote targets are obtained. The results show that the polarization image contains many details and contour information of the target, and the intensity image contains brightness and reflectivity information. Intensity and polarization information complement each other. The characteristics of intensity and polarization images at different spatial frequencies are analyzed for the first time, to our knowledge, by taking advantage of the Fourier modulation mode. We found that the proportion of high-frequency information in the polarization image is much higher than that of the intensity image. The sampling strategy of collecting only low-frequency components is applicable in intensity imaging but needs further improvement in polarization imaging. The polarization SPI lidar system can enrich the target information acquired, improve imaging contrast, and have significant application value for target detection and identification in complex backgrounds.