Parallel compressive super-resolution imaging with wide field-of-view based on physics enhanced network

Parallel compressive super-resolution imaging has attracted increasing attention in recent years. However, the super-resolution quality depends on modulation masks and reconstruction algorithms. A deep-learning method provides an efficient solution, but in wide field-of-view (FOV) scenarios, the dif...

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Veröffentlicht in:	Applied physics letters 2024-05, Vol.124 (21)
Hauptverfasser:	Jin, Xiao-Peng, Xiong, An-Dong, Liu, Fan, Wang, Xiao-Qing, Zhang, Wei, Li, Chang-Heng, Yao, Xu-Ri, Liu, Xue-Feng, Zhao, Qing
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Complexity Field of view Image reconstruction Image resolution Machine learning Masks Modulation Optical transfer function Pixels Signal to noise ratio
Online-Zugang:	Volltext
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