Improving Imaging Quality of Real-time Fourier Single-pixel Imaging via Deep Learning

Volume: 19, Issue: 19, Pages: 4190 - 4190
Published: Sep 27, 2019
Abstract
Fourier single pixel imaging (FSPI) is well known for reconstructing high quality images but only at the cost of long imaging time. For real-time applications, FSPI relies on under-sampled reconstructions, failing to provide high quality images. In order to improve imaging quality of real-time FSPI, a fast image reconstruction framework based on deep learning (DL) is proposed. More specifically, a deep convolutional autoencoder network with...
Paper Details
Title
Improving Imaging Quality of Real-time Fourier Single-pixel Imaging via Deep Learning
Published Date
Sep 27, 2019
Journal
Volume
19
Issue
19
Pages
4190 - 4190
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