Abstract

The influence of sparsity property of images on ghost imaging via sparsity constraints (GISC) is investigated. We find experimentally that the reconstruction quality is in proportion to the sparse ratio of images. Employing the method of representation transform to obtain different sparsity properties for the same object, the effect of three sparse representation bases on the quality of GISC is also discussed.

©2012 Optical Society of America

Multiple-input ghost imaging via sparsity constraints

Wenlin Gong and Shensheng Han
J. Opt. Soc. Am. A 29(8) 1571-1579 (2012)

Experimental investigation of the quality of ghost imaging via sparsity constraints

Wenlin Gong, Zunwang Bo, Enrong Li, and Shensheng Han
Appl. Opt. 52(15) 3510-3515 (2013)

Morphology separation in ghost imaging via sparsity constraint

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