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.
A decline in imaging quality will occur when the sampling data of ghost imaging is recorded by binarization. Based on the Otsu binarization, a method named Otsu binary ghost imaging (OBGI) is proposed to enhance imaging quality. Both theoretical and experimental results show that, with an appropriate threshold value, OBGI can enhance imaging quality significantly when compared with ordinary binary ghost imaging, even providing better imaging quality than that of traditional ghost imaging. It is also shown the method is more applicable under the conditions of low-light level and with a complicated object.
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