Point-spread function in ghost imaging system with thermal light

Fast focusing method in ghost imaging with a tracking trajectory

The imaging environment is unstable for trembling disturbance, which is detrimental to object reconstruction. In this Letter, we experimentally investigated ghost imaging (GI) under a temporal trembling disturbance. The fast-focusing method based on imaging with small sampling measurements is proposed, and the theoretical model and algorithm are validated. It is demonstrated that the proposed method is effective to obtain a better-resolution image of the object under the strong trembling disturbance including a laboratory and a real trembling environment. The results provide a promising approach to deal with image degradation caused by an unstable environment and can find potential applications for ghost imaging in remote sensing.

Ghost imaging lidar system for remote imaging

Research towards practical applications of ghost imaging lidar system especially in longer sensing distance has been urgent in recent years. In this paper we develop a ghost imaging lidar system to boost an extension of remote imaging, where the transmission distance of the collimated pseudo-thermal beam can be improved hugely over long range and just shifting the adjustable lens assembly generates wide field of view suiting for short-range imaging. Based on the proposed lidar system, the changing tendency of illuminating field of view, energy density, and reconstructed images is analyzed and verified experimentally. Some considerations on the improvement of this lidar system are also discussed.

Computational Ghost Imaging Based on Light Source Formed by Coprime Array

In computational ghost imaging, a spatial light modulator (SLM) can be used to modulate the light field. The relative locations and the number of light point pixels on an SLM affect the imaging quality. Usually, SLMs are two-dimensional arrays which are drawn uniformly or are randomly sparse. However, the patterns formed by a uniform array are periodic when the number of light point pixels is small, and the images formed by a random sparse array suffer from large background noise. In this paper, we introduce a coprime array based on the Eisenstein integer to optimize the light point pixel arrangement. A coprime array is widely used as a microwave radar receiving array, but less implemented in optics. This is the first time that a coprime array based on Eisenstein integer has been introduced in computational ghost imaging. A coprime array with this structure enhances the imaging quality when limited measurements are recorded, and it reduces background noise and avoids periodicity. All results are verified by numerical simulation.

Ghost imaging for detecting trembling with random temporal changing

The imaging environment can be destabilized for moving objects and imaging platforms, thus leading the detection to be random trembling, which is detrimental to object reconstruction. In this Letter, we experimentally investigate ghost imaging for detecting trembling with random temporal changing, and an improvement method based on the temporal property of the imaging process is proposed. It is demonstrated that this method is effective in addressing image degradation due to the trembling disturbance and obtaining a higher-quality image of the object. The results provide a promising approach to deal with image degradation caused by an unstable environment and can find potential applications for ghost imaging in remote sensing.