Open AccessOn the recovery conditions for practical ghost imaging with AMP algorithm
Author(s) -
Jiying Liu
Publication year - 2018
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.26.020519
Subject(s) - algorithm , speckle pattern , computer science , matrix (chemical analysis) , ghost imaging , independent and identically distributed random variables , bounded function , laplace distribution , row and column spaces , optics , row , laplace transform , artificial intelligence , mathematics , physics , random variable , statistics , mathematical analysis , materials science , database , composite material
The approximate message passing algorithm (AMP) is introduced for practical ghost imaging (GI). This paper proposes to use preconditioning to modified the sensing matrix such that it satisfies the assumptions of the original AMP algorithm. Furthermore, this paper points out that the speckles used in practical GI system are spatially correlated, and this will degrade the imaging performance. The parameter estimations of exponential power distribution reveal that the rows of modified sensing matrix are indeed bounded by the Laplace distribution, which is heavy-tailed. Then, the recovery conditions for such sensing matrix are investigated. Finally, the semi-real experiments and real data processing have validated the proposed imaging method and shown that the required number of measurements for correlated speckles are significantly greater than independent and identically distributed (i.i.d.) measurement. The results of this paper can be used to guide the design of practical GI remote sensing systems.