Indirect spectrum measurement via random phase modulation and detection in temporal domain.

Spectroscopy continues to provide possibilities for a deeper understanding of fundamental physical phenomena. Traditional spectral measurement method, dispersive Fourier transformation, is always limited by its realization condition (detection in the temporal far-field). Inspired by Fourier ghost imaging, we put forward an indirect spectrum measurement to overcome the limitation. The spectrum information is reconstructed via random phase modulation and near-field detection in the time domain. Since all operations are realized in the near-field region, the required length of dispersion fiber and optical loss are greatly reduced. Considering the application in spectroscopy, the length of required dispersion fiber, the spectrum resolution, the range of spectrum measurement and the requirement on bandwidth of photodetector are investigated.

Image recovery of ghost imaging with sparse spatial frequencies.

When the spatial frequencies of the object are insufficiently sampled, the reconstruction of ghost imaging will suffer from repetitive visual artifacts, which cannot be effectively tackled by existing ghost imaging reconstruction techniques. In this Letter, extensions of the CLEAN algorithm applied in ghost imaging are explored to eliminate those artifacts. Combined with the point spread function estimation using the second-order coherence measurement in ghost imaging, our modified CLEAN algorithm is demonstrated to have a fast and noteworthy improvement against the spatial-frequency insufficiency, even for the extreme sparse sampling cases. A brief explanation of the algorithm and performance analysis are given.

Tracking and imaging of moving objects with temporal intensity difference correlation.

At present, a large number of samplings are required to reconstruct an image of the objects in ghost imaging. When imaging moving objects, it will be hard to perform enough samplings during the moment when the objects can be taken as immobile, causing the reconstructed image of the objects deteriorating. In this paper, we propose a temporal intensity difference correlation ghost imaging scheme, in which a high-quality image of the moving objects within a complex scene can be extracted with much fewer samplings. The spatial sparsity of the moving objects is utilized, while only a linear algorithm is required. This method decreases the number of required samplings, thus relaxing the requirement on high refresh frequency of illumination source and high speed detector, to obtain the information of moving objects with ghost imaging.

Ghost imaging normalized by second-order coherence.

Towards improvements in the quality of reconstructed images, the errors in the point spread function of a ghost imaging system caused by a limited number of samplings and imperfect illumination are discussed. We propose an algorithm by normalizing with the second-order coherence of the illumination field, with which the errors caused by imperfect illumination can be reduced, such as non-uniform spatial distribution of the average intensity, spatially varying profile of the second-order degree of coherence, or power fluctuation.

Detecting fast signals beyond bandwidth of detectors based on computational temporal ghost imaging.

Measurement of fast signal is getting more and more important in many fields. In this paper, we propose to detect a temporal signal based on the idea of computational ghost imaging (GI), which can greatly reduce requirements on bandwidth of detectors. In experiments, we implement retrieving of a temporal signal with time scale of 50ns using a detector of 1kHz bandwidth, which is much lower than the requirement on bandwidth of detector according to information theory. The performance of our technique are also investigated under different detection bandwidths.

Is ghost imaging intrinsically more powerful against scattering?

We demonstrated experimental comparison between ghost imaging and traditional non-correlated imaging under disturbance of scattering. Ghost imaging appears more robust. The quality of ghost imaging does not change much when the scattering is getting stronger, while that of traditional imaging declines dramatically. A concise model is developed to explain the superiority of ghost imaging. Due to its robustness against scattering, ghost imaging will be useful in harsh environment.