Single-pixel imaging, which is also known as computational ghost imaging, can reconstruct an entire image using one non-spatially resolved detector. However, it often requires a large amount of sampling, severely limiting its application. In this paper, we discuss the implementation of secured regions of interest (SROIs) in single-pixel imaging and illustrate its application using two experiments. Under a limited number of sampling times, we improved the resolution and recovered spectral information of interest in the ROI. Meanwhile, this scheme has high information security with high encryption and has great potential for single-pixel video and compressive multi-spectral single-pixel imaging.

In previous single-pixel imaging systems, the light source was generally idle with respect to time. Here, we propose a novel image fusion and visible watermarking scheme based on Fourier single-pixel imaging (FSPI) with a multiplexed time-varying (TV) signal, which is generated by the watermark pattern hidden in the light source. We call this scheme as TV-FSPI. With TV-FSPI, we can realize high-quality visible image watermarking, encrypted image watermarking and full-color visible image watermarking. We also discuss the extension to invisible watermarking based on TV-FSPI. Furthermore, we don't have to recode illumination patterns, because TV-FSPI can be extended to existing mainstream illumination patterns, such as random illumination mode and Hadamard illumination mode. Thus TV-FSPI has the potential to be used in single-pixel broadcasting system and multi-spectral single-pixel imaging system.

A new method is proposed to improve the signal-to-noise ratio (SNR) of regions of interest (ROIs) in a ghost imaging (GI) system with uneven speckle illumination. The imaging results in a GI system can be distorted when there is an uneven distribution of light. In this study, three thin-film polarizers are used to create illumination patterns in uneven light intensity distribution. In particular, the polarizer set is loaded on the object arm only, that is, the original uniformly distributed light field is still acquired by the reference arm. This small change in the light path eliminates the distortion caused by uneven illumination while increasing the SNR of the ROI. This strategy has been confirmed in principle and through simulation and experiments.

Ghost imaging (GI) is an imaging method that uses photon correlation for image restoration. In this study, we design two different color speckle fields and use a digital light projector to display them onto a color object that is measured by a single-pixel photodetector. The first is uniformly distributed with red, green, and blue colors, while patterns are generated through linear mapping of a Hadamard matrix in the second. We evaluated three original image reconstruction schemes based on multi-color speckle (MS) pattern: traditional ghost imaging and pseudo-inverse ghost imaging based on uniform speckle field and single-pixel imaging (MS-HSI) based on Hadamard matrix linear mapping speckle field. Simulation and experimental results show that these methods can effectively restore color objects. We also compare the advantages and disadvantages of the three methods, and optimize the GI strategy of color objects. Among the three methods, the background noise of MS-HSI based on Hadamard matrix linear mapping is lower, more details are retained, and the signal-to-noise ratio is the highest.

This study proposes two methods of optical watermarking based on multiplexed time-varying signals for computational ghost imaging using the Hadamard matrices. The proposed methods can realize image fusion and dual optical encryption. The time-varying signal is encoded into a specific Hadamard coefficient in advance and hidden in the light source of the transmitting end as a multiplicative factor or loaded at the receiving end as an additive factor. Theory and experiments confirm the feasibility of this scheme. Moreover, the scheme is highly scalable and has potential applications in multispectral single-pixel imaging.