The source’s energy fluctuation has a great effect on the quality of single-pixel imaging (SPI). When the method of complementary detection is introduced into an SPI camera system and the echo signal is corrected with the summation of the light intensities recorded by two complementary detectors, we demonstrate, by both experiments and simulations, that complementary single-pixel imaging (CSPI) is robust to the source’s energy fluctuation. The superiority of the CSPI structure is also discussed in comparison with previous SPI via signal monitoring.

The influence of the sparsity of random speckle illumination on traditional ghost imaging (GI) and GI via sparsity constraint (GISC) in a noise environment is investigated. The experiments demonstrate that both GI and GISC obtain their best imaging quality when the sparsity of random speckle illumination is 0.5, which is also explained by some parameters such as detection of the signal to noise ratio and mutual coherence of the measurement matrix.

We propose a color ghost imaging approach where the object is illuminated by three-color non-orthogonal random patterns. The object’s reflection/transmission information is received by only one single-pixel detector, and both the sparsity constraint and non-local self-similarity of the object are utilized in the image reconstruction process. Numerical simulation results demonstrate that the imaging quality can be obviously enhanced by ghost imaging via sparsity constraint and non-local self-similarity (GISCNL), compared with the reconstruction methods where only the object’s sparsity is used. Factors affecting the quality of GISCNL, such as the measurement number and the detection signal-to-noise ratio, are also studied.

The performances of ghost imaging and conventional imaging in photon shot noise cases are investigated. We define an imaging signal-to-noise ratio called SNR^tran where only the object’s transmission region is used to evaluate the imaging quality and it can be applied to ghost imaging (GI) with any random pattern. Both the values SNRGItran of GI and SNRCItran of conventional imaging in photon shot noise cases are deduced from a simple statistical analysis. The analytical results, which are backed up by numerical simulations, demonstrate that the value SNRGItran is related to the ratio between the object’s transmission area A_o and the number density of photons illuminating the object plane I_o, which is similar to the theoretical results based on the first principle of GI with a Gaussian speckle field deduced by B. I. Erkmen and J. H. Shapiro [in Adv. Opt. Photonics 2, 405–450 (2010)]. In addition, we also show that the value SNRCItran will be larger than SNRGItran when A_o is beyond a threshold value.

We investigate the influence of the source’s energy fluctuation on both computational ghost imaging and computational ghost imaging via sparsity constraint, and if the reconstruction quality will decrease with the increase of the source’s energy fluctuation. In order to overcome the problem of image degradation, a correction approach against the source’s energy fluctuation is proposed by recording the source’s fluctuation with a monitor before modulation and correcting the echo signal or the intensity of computed reference light field with the data recorded by the monitor. Both the numerical simulation and experimental results demonstrate that computational ghost imaging via sparsity constraint can be enhanced by correcting the echo signal or the intensity of computed reference light field, while only correcting the echo signal is valid for computational ghost imaging.