Abstract
Ghost imaging (GI) is a method to nonlocally image an object with a single-pixel detector. However, the speckle's transverse size at the object plane limits the system's imaging resolution for conventional GI linear reconstruction algorithm. By combining the sparsity constraint of imaging object with ghost imaging method, we demonstrate experimentally that ghost imaging via sparsity constraint (GISC) can dramatically enhance the imaging resolution even using the random measurements far below the Nyquist limit. The image reconstruction algorithm of GISC is based on compressive sensing. Factors affecting the reconstruction quality of high-resolution GISC, such as the receiving system's numerical aperture and the object's sparse representation basis, are also investigated experimentally. This high-resolution imaging technique will have great applications in the microscopy and remote-sensing areas.
Highlights
IntroductionThe image’s sparsity has been taken as a quite general assumption, a compressive sensing (CS) technique enables the reconstruction of an N-pixel image from much fewer than N global random measurements[23,24]
Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, 201800, China
When compressive sensing (CS) is applied to the image reconstruction of Ghost imaging (GI), highresolution far-field ghost imaging via sparsity constraint (GISC) is possible with the use of random measurement below Nyquist limit because a natural object can be sparsely expressed in a proper representation basis[23,24]
Summary
The image’s sparsity has been taken as a quite general assumption, a compressive sensing (CS) technique enables the reconstruction of an N-pixel image from much fewer than N global random measurements[23,24] This technique has already been successfully applied to super-resolution imaging[25,26], remote sensing[27,28], and compressive imaging[29,30,31]. When CS is applied to the image reconstruction of GI, highresolution far-field ghost imaging via sparsity constraint (GISC) is possible with the use of random measurement below Nyquist limit because a natural object can be sparsely expressed in a proper representation basis (or under a suitable basis transform)[23,24]
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