Correspondence Fourier-transform ghost imaging

Fourier-transform ghost imaging (FGI) enables us to realize diffraction imaging within the Fresnel region by calculating the second-order correlations of light fields. Existing FGI schemes reconstruct the Fourier frequency spectrum via correlation or sparsity constraints, which generally require object-arm detection values with relatively high signal-to-noise ratio. In this paper, we propose a correspondence FGI scheme, which reconstructs the object's Fourier spectrum by averaging partial reference patterns corresponding to object-arm detection values of high fluctuations. This conditional-averaging method is theoretically demonstrated and then explored and verified by both simulation and experiment. Moreover, an information-theory-based explanation of the simulation results is performed by studying the Fisher information of detection signals. The proposed scheme improves the sampling efficiency and is expected to expand the application of FGI by combining it with other reconstruction techniques.

Automated summary

The paper introduces a novel Fourier-transform ghost imaging scheme that reconstructs the Fourier spectrum of the object by averaging partial reference patterns with high fluctuations in object-arm detection values, improving sampling efficiency, and expanding the application of FGI by combining it with other reconstruction techniques.