Preconditioned deconvolution method for high-resolution ghost imaging

Abstract

Ghost imaging (GI) can nonlocally image objects by exploiting the fluctuation characteristics of light fields, where the spatial resolution is determined by the normalized second-order correlation function g ( 2 ) . However, the spatial shift-invariant property of g ( 2 ) is distorted when the number of samples is limited, which hinders the deconvolution methods from improving the spatial resolution of GI. In this paper, based on prior imaging systems, we propose a preconditioned deconvolution method to improve the imaging resolution of GI by refining the mutual coherence of a sampling matrix in GI. Our theoretical analysis shows that the preconditioned deconvolution method actually extends the deconvolution technique to GI and regresses into the classical deconvolution technique for the conventional imaging system. The imaging resolution of GI after preconditioning is restricted to the detection noise. Both simulation and experimental results show that the spatial resolution of the reconstructed image is obviously enhanced by using the preconditioned deconvolution method. In the experiment, 1.4-fold resolution enhancement over Rayleigh criterion is achieved via the preconditioned deconvolution. Our results extend the deconvolution technique that is only applicable to spatial shift-invariant imaging systems to all linear imaging systems, and will promote their applications in biological imaging and remote sensing for high-resolution imaging demands.

On Ghost Imaging Studies for Information Optical Imaging

“…Similar to the typical deconvolution operation [85,86] for traditional imaging that exploits the prior information of the system's transmission function, it is possible to achieve spatial super-resolution imaging in GI. By performing regularized preconditioning operations [87][88][89] on both the detection signal as well as the transmission matrix and solving the preconditioned problem via optimization algorithms, it is experimentally demonstrated that a high-quality imaging result with resolution beyond the diffraction limit can be obtained, and further theoretical analysis from the perspective of Fourier frequency domain also verifies its capability [90].…”

Improving the Resolution of Correlation Imaging via the Fluctuation Characteristics

“…Li et al used localization and thresholding to reduce the effect of the PSF in a correlation imaging system [32]. Preconditioned deconvolution methods [33] and the use of the coefficient of skewness [34] have been also suggested. Among the schemes based on image reconstruction, compressed sensing correlation imaging reduced the effect of the PSF on the imaging quality, using sparsity constraints to improve the spatial resolution of correlation imaging [24,[35][36][37].…”

Second-order cumulants ghost imaging

“…The narrowing of PSF by higher-order correlation of non-Rayleigh speckle fields has been reported [31] . Other schemes to enhance the resolution of GI have also been suggested, such as spatial low-pass filtering [18,20] , localizing and thresholding [32] , preconditioned deconvolution methods [33] , optical random speckle encoding based on hybrid wavelength and phase modulation scheme [34] , deep neural network constraints [35] , and speeded up robust features new sum of modified Laplacian (SURF-NSML) [36] .…”