Spatial multiplexing reconstruction for Fourier-transform ghost imaging via sparsity constraints.

A spatial multiplexing reconstruction method has been proposed to improve the sampling efficiency and image quality of Fourier-transform ghost imaging. In this method, the sensing equation of Fourier-transform ghost imaging is established based on recombination and reutilization of the correlated intensity distributions of light fields. It is theoretically proved that the scale of the sensing matrix in the sensing equation can be greatly reduced, and spatial multiplexing combined with this matrix reduction provides the feasibility of ghost imaging with just a few measurements. Experimental results show better visibility and signal-to-noise ratio in the Fourier spectrums reconstructed via spatial multiplexing compared with previous methods. The transmittance of an object is also recovered in spatial domain with better image quality based on its spectrum of spatial multiplexing reconstruction. This method is especially important to x-ray ghost imaging applications due to its potential for reducing radiation damage and achieving high quality images in x-ray microscopy.