Sub-Rayleigh imaging via undersampling scanning based on sparsity constraints

doi:10.1088/1674-1056/26/2/024203

Abstract We demonstrate that, by undersampling scanning object with a reconstruction algorithm related to compressed sensing, an image with the resolution exceeding the finest resolution defined by the numerical aperture of the system can be obtained. Experimental results show that the measurements needed to achieve sub-Rayleigh resolution enhancement can be less than 10% of the pixels of the object. This method offers a general approach applicable to point-by-point illumination super-resolution techniques.

Keywords: super-resolution image reconstruction techniques

Received: 29 August 2016
Revised: 11 October 2016
Accepted manuscript online:

PACS:	42.40.Lx	(Diffraction efficiency, resolution, and other hologram characteristics)
	42.30.Va	(Image forming and processing)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61605218 and 61601442), the National Defense Science and Technology Innovation Foundation of the Chinese Academy of Sciences (Grant No. CXJJ-16S047), and the National Major Scientific Instruments Development Project of China (Grant No. 2013YQ030595).

Corresponding Authors: Xu-Ri Yao, Xiao-Yong Guo
E-mail: yaoxuri@aliyun.com;xyguo@nssc.ac.cn

Cite this article:

Chang-Bin Xue(薛长斌), Xu-Ri Yao(姚旭日), Long-Zhen Li(李龙珍), Xue-Feng Liu(刘雪峰), Wen-Kai Yu(俞文凯), Xiao-Yong Guo(郭晓勇), Guang-Jie Zhai(翟光杰), Qing Zhao(赵清) Sub-Rayleigh imaging via undersampling scanning based on sparsity constraints 2017 Chin. Phys. B 26 024203

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