Zero Deep Curve 추정방식을 이용한 저조도에 강인한 비디오 개선 방법

Recently, object recognition using image/video signals is rapidly spreading on autonomous driving and mobile phones. However, the actual input image/video signals are easily exposed to a poor illuminance environment. A recent researches for improving illumination enable to estimate and compensate th...

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Bibliographic Details
Published in멀티미디어학회논문지 Vol. 25; no. 8; pp. 991 - 998
Main Authors 최형석(Hyeong-Seok Choi), 양윤기(Yoon Gi Yang)
Format Journal Article
LanguageKorean
Published 한국멀티미디어학회 2022
Subjects
전자/정보통신공학
Low Light Image
Fast Algorithm
Video Processing
Image Enhancement
Deep Learning
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Summary:Recently, object recognition using image/video signals is rapidly spreading on autonomous driving and mobile phones. However, the actual input image/video signals are easily exposed to a poor illuminance environment. A recent researches for improving illumination enable to estimate and compensate the illumination parameters. In this study, we propose VE-DCE (video enhancement zero-reference deep curve estimation) to improve the illumination of low-light images. The proposed VE-DCE uses unsupervised learning-based zero-reference deep curve, which is one of the latest among learning based estimation techniques. Experimental results show that the proposed method can achieve the quality of low-light video as well as images compared to the previous method. In addition, it can reduce the computational complexity with respect to the existing method.
Bibliography:KISTI1.1003/JNL.JAKO202226258536914
ISSN:1229-7771
2384-0102