The multi-sensor system based on single pixel imaging can realize the simultaneous measurement and imaging of various optical information (such as spectrum, polarization, etc.), in which a single pixel sensor can measure one kind of optical information. Spectral imaging technology can simultaneously obtain rich information such as spatial structure and fine spectral characteristics of the target scene. The architecture and implementation of most spectral imaging systems are complex, which limits or affects their indicators, parameters, and applications to varying degrees. Here, we propose a novel multispectral single pixel imaging method based on spatial and spectral dimension decoupling. This method uses spatial dimension compression coding modulation, and spectral dimension modulation through ingenious optical system design. It utilizes a single pixel detector array combined with traditional spectral filtering technology to directly and parallel collect spatial image compression coding information from various spectral channels. This method reduces the information carrying capacity of a single photon and reduces the requirements for detection signal to noise ratio. The experiment demonstrated 15 channels of visible and near-infrared spectral single pixel imaging and demonstrated real-time multispectral single pixel imaging with an imaging speed of 5 Hz, which can be extended to spectral imaging with higher spectral resolution and more spectral channels. This work can facilitate the use of multi-sensor arrays for more convenient research such as spectral information acquisition.

Sign language is the main means of communication for deaf and mute individuals, special populations, and special situations. However, the current low popularity of sign language has also hindered the deep contact between deaf and mute people and the current society. In order to further promote the application level and service ability of sign language, establish a convenient communication bridge for special populations and scenes, and meet the application requirements of portability, real-time, reliability, and stability, this paper designs a gesture recognition system based on multiple sensors. This system combines transfer learning and has functions such as Bluetooth communication, data acquisition and processing, gesture recognition, and result display. The transfer experiment results showed that the accuracy of gesture recognition reached 94.07% and 92.53%, respectively, which were 9.41% and 11.73% higher than before the transfer. Moreover, the accuracy and stability of gesture recognition were improved through transfer learning, and the universality and robustness of the model were improved. Through the testing and gesture recognition experiments of the gesture recognition system, it has been shown that the recognition system can recognize gesture movements of different groups of people, with good recognition rate and stability.

Computational ghost imaging (Computational GI) is a method of acquiring object information by measuring light field intensity, which would be used to achieve imaging in a complicated environment. The main issue to be addressed in computational GI technology is how to achieve rapid and high-quality imaging while assuring the secure transmission of detection data in practical distant imaging applications. In order to address the mentioned issues, this paper proposes a remote secure computational GI method based on quantum communication technology. Using the quantum key distribution (QKD) network, the computational GI system can be reconstructed while solving the problem of information security transmission between the detector and the reconstructed computing device. By exploring the influence of different random measurement matrices on the quality of image reconstruction, it is found that the randomness of the matrix is positively correlated with the imaging quality. The higher the randomness, the higher the imaging quality. Based on this discovery, a new type of quantum cryptography measurement matrix is constructed using quantum cryptography with high randomness. In addition, through further orthogonalization and normalization of the matrix, the matrix has both good randomness and orthogonality, and high-quality imaging results can be obtained at a low sampling rate. The feasibility and effectiveness of the method are verified by random detection, numerical simulation, and simulation imaging experiments. Compared with the traditional computational GI system, the method proposed in this paper has higher transmission security, rapid imaging, and high-quality imaging under this premise, which provides a new idea for the practical development of computational GI technology.

As a high-quality imaging scheme, the sampling and reconstruction of 1D Walsh transform ghost imaging is mathematically equivalent to 1D Walsh transform, i.e. single matrix multiplication. It is widely acknowledged that compared with the 1D Walsh transform, the 2D Walsh transform is advantageous in terms of simpler calculation and stronger energy concentration. However, the 2D Walsh transform cannot adapt well to 1D imaging systems because it requires matrix multiplication to be carried out twice. To address this problem, we employ the ‘most natural’ Walsh order basis patterns to obtain the bucket detection value, so that the effect of the 1D sampling process is the same as that in the 2D Walsh transform. Based on this relationship of equivalence, this scheme can recover the image accurately. Numerical simulations and experimental results demonstrate that 2D Walsh transform ghost imaging is capable of reconstructing a sharp image with fewer coefficients. Moreover, we propose a fast algorithm for the 2D Walsh transform, which is proven to require less reconstruction time than the 1D fast Walsh transform. We are committed to building an efficient imaging system that can save as much time as possible in both sampling and reconstruction. From a practical point of view, a broader application may be found in real-time and low-resolution video imaging.