Gradual ghost imaging of moving objects by tracking based on cross correlation.

The requirement of a large number of samplings limits the performance of ghost imaging for moving objects. Conventionally, tracking and imaging of the moving objects are done independently; thus, sequential clear images of the moving target during its evolution are required. In this Letter, we propose to obtain the displacement of the object via cross correlation between sequential unclear rough images. Then, a high-quality image of the moving object can be reconstructed gradually during its evolution. Our method works well for translating and rotating objects.

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.