Wide-field scanning ghost imaging based on a local binary pattern and untrained neural network.

Continuous scene imaging is an important research goal in the field of autonomous driving, and the key is to ensure the imaging quality and efficiency. In this paper, we propose a method for information fusion in wide-field scanning ghost imaging using a local binary pattern (LBP) based on deep learning. The initial physical model formed by the LBP integrated into a deep neural network, which effectively enhances the expression of image texture details.

BER performance of an FSOC system over atmospheric turbulence channels based on computational temporal ghost imaging.

In a free space optical communication (FSOC) system, atmospheric turbulence will increase the bit error ratio (BER) and impair FSOC link reliability. Since computational temporal ghost imaging (CTGI) has anti-interference, we present an FSOC system over atmospheric turbulence based on CTGI. The simulation results show that the BER performance of CTGI is better than on-off keying under different atmospheric turbulence regimes.

Highly accurate OAM mode detection network for ring Airy Gaussian vortex beams disturbed by atmospheric turbulence based on interferometry.

Atmospheric turbulence reduces the detection accuracy of orbital angular momentum (OAM) modes, which affects the performance of OAM optical communication. In this paper, we propose a method based on interferometry and a residual network (ResNet) to detect the OAM modes of ring Airy Gaussian vortex beams (RAGVBs) disturbed by atmospheric turbulence. The RAGVBs first interfere with spherical waves to obtain the sign features of the OAM modes, and then ResNet is employed to recognize OAM modes from the interferograms.

Enhancing critical resolution of a ghost imaging system by using a vortex beam.

In an imaging system, resolution and signal-to-noise ratio (SNR) are two important indexes to characterize imaging quality. Ghost imaging is a novel imaging method whose imaging resolution and SNR are affected by the speckle size. In this paper, the relation between speckle size and resolution as well as that between speckle size and SNR in the GI system is analyzed in detail.

Improving the signal-to-noise ratio of computational ghost imaging of a reflective object with a rough surface by Hadamard modulated light field.

We propose an optimization scheme to improve the reconstruction quality of computational ghost imaging (GI) of a reflective target with a rough surface by using the Hadamard modulation light field (HCGI). By comparison with computational GI with a traditional Gaussian light field (GCGI), the signal-to-noise ratio of GCGI is quite bad, and it is difficult to distinguish the imaging signal from the background when the surface roughness of the object is higher, while a ghost image with better quality can be obtained by HCGI. The difference is explained by comparing the distribution of the correlation coefficient.