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Temporal compressive imaging reconstruction based on a 3D-CNN network. | LitMetric
In temporal compressive imaging (TCI), high-speed object frames are reconstructed from measurements collected by a low-speed detector array to improve the system imaging speed. Compared with iterative algorithms, deep learning approaches utilize a trained network to reconstruct high-quality images in a short time. In this work, we study a 3D convolutional neural network for TCI reconstruction to make full use of the temporal and spatial correlation among consecutive object frames. Both simulated and experimental results demonstrate that our network can achieve better reconstruction quality with fewer number of layers.
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