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Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

We present an experimental demonstration of ghost imaging of reflective objects with different surface roughness. The influence of the surface roughness, the transverse size of the test detector, and the reflective angle on the signal-to-noise ratio (SNR) is analyzed by measuring the second-order correlation of the light field based on classical statistical optics. It is shown that the SNR decreases with an increment of the surface roughness and the detector's transverse size or a decrease of the reflective angle. Additionally, the comparative studies between the rough object and the smooth one under the same conditions are also discussed.

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The vibration is one of the important factors affecting imaging quality of conventional remote sensing imaging because the relative motion between the imaging system and the target can result in the degradation of imaging quality. The influence of the vibration of the detector in the test path on reflective ghost imaging (RGI) is investigated theoretically and experimentally. We analyze the effects of the vibrating amplitude and velocity. The results demonstrate that the microvibrations of the bucket detector have almost no impact on the imaging resolution and signal-to-noise ratio (SNR) of RGI, i.e., the degradation of imaging quality caused by the vibration of the detector can be overcome to some extent. Our results can be helpful for remote sensing imaging.