Super-resolution imaging via sparsity constraint and sparse speckle illumination

doi:10.1088/1674-1056/27/7/074202

Abstract We present an imaging approach via sparsity constraint and sparse speckle illumination which can dramatically enhance the optical system's imaging resolution. When the object is illuminated by some sparse speckles and the sparse reconstruction algorithm is utilized to restore the blur image, numerical simulated results demonstrate that the image, whose resolution exceeds the Rayleigh limit, can be stably reconstructed even if the detection signal-to-noise ratio (SNR) is less than 10 dB. Factors affecting the quality of the reconstructed image, such as the coded pattern's sparsity and the detection SNR, are also studied.

Keywords: imaging and optical processing

Received: 05 February 2018
Revised: 19 March 2018
Accepted manuscript online:

PACS:

42.30.-d

(Imaging and optical processing)

Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61571427).

Corresponding Authors: Wenlin Gong
E-mail: gongwl@siom.ac.cn

Cite this article:

Pengwei Wang(王鹏威), Wei Li(李伟), Chenglong Wang(王成龙), Zunwang Bo(薄遵望), Wenlin Gong(龚文林) Super-resolution imaging via sparsity constraint and sparse speckle illumination 2018 Chin. Phys. B 27 074202

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