Compressive sensing computational ghost imaging

被引:144
作者
Katkovnik, Vladimir [1 ]
Astola, Jaakko [1 ]
机构
[1] Tampere Univ Technol, Dept Signal Proc, FIN-33101 Tampere, Finland
基金
芬兰科学院;
关键词
RECONSTRUCTION; OPTIMIZATION; TRANSFORM; IMAGES;
D O I
10.1364/JOSAA.29.001556
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The computational ghost imaging with a phase spatial light modulator (SLM) for wave field coding is considered. A transmission-mask amplitude object is reconstructed from multiple intensity observations. Compressive techniques are used in order to gain a successful image reconstruction with a number of observations (measurement experiments), which is smaller than the image size. Maximum likelihood style algorithms are developed, respectively, for Poissonian and approximate Gaussian modeling of random observations. A sparse and overcomplete modeling of the object enables the advanced high accuracy and sharp imaging. Numerical experiments demonstrate that an approximative Gaussian distribution with an invariant variance results in the algorithm that is efficient for Poissonian observations. (C) 2012 Optical Society of America
引用
收藏
页码:1556 / 1567
页数:12
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