Signal-to-Noise Ratio Improvement for Multiple-Pinhole Imaging Using Supervised Encoder–Decoder Convolutional Neural Network Architecture

Digital image devices have been widely applied in many fields, such as individual recognition and remote sensing. The captured image is a degraded image from the latent observation, where the degradation processing is affected by some factors, such as lighting and noise corruption. Specifically, noi...

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Bibliographic Details
Published in:	Photonics Vol. 9; no. 2; p. 69
Main Authors:	Danan, Eliezer, Shabairou, Nadav, Danan, Yossef, Zalevsky, Zeev
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.02.2022
Subjects:	Aperture Artificial neural networks Cameras coded aperture imaging Coders Compression Computer architecture convolutional neural network Corruption Datasets Deep learning Digital imaging Image degradation Neural networks Object recognition Pinholes Projectors Remote sensing Sensors Signal to noise ratio super-resolution Wiener filtering
ISSN:	2304-6732, 2304-6732
Online Access:	Get full text
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