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Fast compressive measurements acquisition using optimized binary sensing matrices for low-light-level imaging
Jun Ke
, Edmund Y. Lam
光电学院
Science and Technology on Low-Light-Level Night Vision Laboratory
The University of Hong Kong
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探究 'Fast compressive measurements acquisition using optimized binary sensing matrices for low-light-level imaging' 的科研主题。它们共同构成独一无二的指纹。
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Engineering
Signal-to-Noise Ratio
100%
Light Level
100%
Measurement Signal
100%
Experimental Result
50%
Image Reconstruction
50%
Mean Square Error
50%
Imaging Systems
50%
Dynamic Range
50%
Sensor System
50%
Constrained Optimization Problem
50%
Computer Science
Noise-to-Signal Ratio
100%
Lower Light Level
100%
Experimental Result
50%
Optimization Problem
50%
Image Reconstruction
50%
Imaging Systems
50%
Reconstruction Error
50%
Constrained Optimization
50%
Physics
Signal-to-Noise Ratio
100%
Image Reconstruction
50%
Dynamic Range
50%
Data Acquisition
50%
Chemical Engineering
Constrained Optimization
100%