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Fast compressive measurements acquisition using optimized binary sensing matrices for low-light-level imaging
Jun Ke
, Edmund Y. Lam
School of Optics and Photonics
Science and Technology on Low-Light-Level Night Vision Laboratory
The University of Hong Kong
Research output
:
Contribution to journal
›
Article
›
peer-review
16
Citations (Scopus)
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Engineering
Constrained Optimization Problem
50%
Dynamic Range
50%
Experimental Result
50%
Image Reconstruction
50%
Imaging Systems
50%
Light Level
100%
Mean Square Error
50%
Measurement Signal
100%
Sensor System
50%
Signal-to-Noise Ratio
100%
Computer Science
Constrained Optimization
50%
Experimental Result
50%
Image Reconstruction
50%
Imaging Systems
50%
Lower Light Level
100%
Noise-to-Signal Ratio
100%
Optimization Problem
50%
Reconstruction Error
50%
Physics
Data Acquisition
50%
Dynamic Range
50%
Image Reconstruction
50%
Signal-to-Noise Ratio
100%
Chemical Engineering
Constrained Optimization
100%