Visible and near-infrared separation using conditional generative adversarial network

Visible and near-infrared image acquisition using a single conventional image sensor helps simpler implementation on mobile devices. This paper presents a signal separation method of visible and near-infrared images from an image which has mixed visible and near-infrared signals captured by a single...

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Bibliographic Details
Published in2018 International Conference on Electronics, Information, and Communication (ICEIC) pp. 1 - 2
Main Authors Park, Younghyeon, Jeon, Byeungwoo
Format Conference Proceeding
LanguageEnglish
Published Institute of Electronics and Information Engineers 01.01.2018
Subjects
generative adversarial network
machine learning
near-infrared
NIR
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Summary:Visible and near-infrared image acquisition using a single conventional image sensor helps simpler implementation on mobile devices. This paper presents a signal separation method of visible and near-infrared images from an image which has mixed visible and near-infrared signals captured by a single CMOS sensor. In the separation process, the conditional generative adversarial network is applied to extract each visible and near-infrared image from the mixed one. For the experiment, a conventional digital camera is used with a simple modification. The experimental result shows that the proposed method well extracts both visible and near-infrared images.
DOI:10.23919/ELINFOCOM.2018.8330670