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2018 | OriginalPaper | Chapter

Stripe Noise Correction for Infrared Imaging System Using Neural Network Theory

Authors : Junqi Bai, Chuanwen Chang, Wen Liu

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

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Abstract

For staring infrared image, there is inevitable stripe noise which seriously degrades the quality of the image. In this paper, a stripe noise correction is proposed using high frequency neural network theory. Firstly, the mechanism of production for stripe noise is discussed; secondly, the correction model of high frequency neural network is established, the gain and offset parameters are estimated; finally, stripe noise is corrected. Experimental results of real and simulated images show that the proposed method can correct stripe noise effectively, without producing ghosting artifacts.

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Metadata
Title
Stripe Noise Correction for Infrared Imaging System Using Neural Network Theory
Authors
Junqi Bai
Chuanwen Chang
Wen Liu
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Computer Science and Ubiquitous Computing

Print ISBN: 978-981-10-7604-6

Electronic ISBN: 978-981-10-7605-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7605-3_109