Transparent Object Reconstruction Based on Compressive Sensing and Super-Resolution Convolutional Neural Network

Transparent Object Reconstruction Based on Compressive Sensing and Super-Resolution Convolutional Neural Network

Abstract The detection and reconstruction of transparent objects have remained challenging due to the absence of their features and variations in the local features with variations in illumination. In this paper, both compressive sensing (CS) and super-resolution convolutional neural network (SRCNN)...

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Bibliographic Details
Main Authors: Anumol Mathai, Li Mengdi, Stephen Lau, Ningqun Guo, Xin Wang
Format: Article
Language:English
Published: SpringerOpen 2022-04-01
Series:Photonic Sensors
Subjects:
Transparent object imaging
single-pixel imaging
compressive sensing
total-variation minimization
SRCNN algorithm
Online Access:https://doi.org/10.1007/s13320-022-0653-x

Internet

https://doi.org/10.1007/s13320-022-0653-x

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